Brain templates and atlases.

PubMed

Evans, Alan C; Janke, Andrew L; Collins, D Louis; Baillet, Sylvain

2012-08-15

The core concept within the field of brain mapping is the use of a standardized, or "stereotaxic", 3D coordinate frame for data analysis and reporting of findings from neuroimaging experiments. This simple construct allows brain researchers to combine data from many subjects such that group-averaged signals, be they structural or functional, can be detected above the background noise that would swamp subtle signals from any single subject. Where the signal is robust enough to be detected in individuals, it allows for the exploration of inter-individual variance in the location of that signal. From a larger perspective, it provides a powerful medium for comparison and/or combination of brain mapping findings from different imaging modalities and laboratories around the world. Finally, it provides a framework for the creation of large-scale neuroimaging databases or "atlases" that capture the population mean and variance in anatomical or physiological metrics as a function of age or disease. However, while the above benefits are not in question at first order, there are a number of conceptual and practical challenges that introduce second-order incompatibilities among experimental data. Stereotaxic mapping requires two basic components: (i) the specification of the 3D stereotaxic coordinate space, and (ii) a mapping function that transforms a 3D brain image from "native" space, i.e. the coordinate frame of the scanner at data acquisition, to that stereotaxic space. The first component is usually expressed by the choice of a representative 3D MR image that serves as target "template" or atlas. The native image is re-sampled from native to stereotaxic space under the mapping function that may have few or many degrees of freedom, depending upon the experimental design. The optimal choice of atlas template and mapping function depend upon considerations of age, gender, hemispheric asymmetry, anatomical correspondence, spatial normalization methodology and disease

A mesoscale connectome of the mouse brain

PubMed Central

Oh, Seung Wook; Harris, Julie A.; Ng, Lydia; Winslow, Brent; Cain, Nicholas; Mihalas, Stefan; Wang, Quanxin; Lau, Chris; Kuan, Leonard; Henry, Alex M.; Mortrud, Marty T.; Ouellette, Benjamin; Nguyen, Thuc Nghi; Sorensen, Staci A.; Slaughterbeck, Clifford R.; Wakeman, Wayne; Li, Yang; Feng, David; Ho, Anh; Nicholas, Eric; Hirokawa, Karla E.; Bohn, Phillip; Joines, Kevin M.; Peng, Hanchuan; Hawrylycz, Michael J.; Phillips, John W.; Hohmann, John G.; Wohnoutka, Paul; Gerfen, Charles R.; Koch, Christof; Bernard, Amy; Dang, Chinh; Jones, Allan R.; Zeng, Hongkui

2016-01-01

Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease. PMID:24695228

A pediatric brain structure atlas from T1-weighted MR images

NASA Astrophysics Data System (ADS)

Shan, Zuyao Y.; Parra, Carlos; Ji, Qing; Ogg, Robert J.; Zhang, Yong; Laningham, Fred H.; Reddick, Wilburn E.

2006-03-01

In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. We constructed a 3D triangular mesh model for each structure by triangulation of the structure's reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/BrainAtlas) can be used to plan treatment, to conduct knowledge and modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.

Combining multi-atlas segmentation with brain surface estimation

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Carass, Aaron; Resnick, Susan M.; Pham, Dzung L.; Prince, Jerry L.; Landman, Bennett A.

2016-03-01

Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this "segmentation to surface to parcellation" strategy has shown limitation in various situations. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.

Combining Multi-atlas Segmentation with Brain Surface Estimation.

PubMed

Huo, Yuankai; Carass, Aaron; Resnick, Susan M; Pham, Dzung L; Prince, Jerry L; Landman, Bennett A

2016-02-27

Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this "segmentation to surface to parcellation" strategy has shown limitations in various situations. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

PubMed

Liyanage, Kishan Andre; Steward, Christopher; Moffat, Bradford Armstrong; Opie, Nicholas Lachlan; Rind, Gil Simon; John, Sam Emmanuel; Ronayne, Stephen; May, Clive Newton; O'Brien, Terence John; Milne, Marjorie Eileen; Oxley, Thomas James

2016-01-01

Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution) MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap) to 1 (complete overlap). For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

Atlas-Guided Segmentation of Vervet Monkey Brain MRI

PubMed Central

Fedorov, Andriy; Li, Xiaoxing; Pohl, Kilian M; Bouix, Sylvain; Styner, Martin; Addicott, Merideth; Wyatt, Chris; Daunais, James B; Wells, William M; Kikinis, Ron

2011-01-01

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model. PMID:22253661

A review of structural and functional brain networks: small world and atlas.

PubMed

Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Moore, Philip; Zheng, Jiaxiang

2015-03-01

Brain networks can be divided into two categories: structural and functional networks. Many studies of neuroscience have reported that the complex brain networks are characterized by small-world or scale-free properties. The identification of nodes is the key factor in studying the properties of networks on the macro-, micro- or mesoscale in both structural and functional networks. In the study of brain networks, nodes are always determined by atlases. Therefore, the selection of atlases is critical, and appropriate atlases are helpful to combine the analyses of structural and functional networks. Currently, some problems still exist in the establishment or usage of atlases, which are often caused by the segmentation or the parcellation of the brain. We suggest that quantification of brain networks might be affected by the selection of atlases to a large extent. In the process of building atlases, the influences of single subjects and groups should be balanced. In this article, we focused on the effects of atlases on the analysis of brain networks and the improved divisions based on the tractography or connectivity in the parcellation of atlases.

Tumor growth model for atlas based registration of pathological brain MR images

NASA Astrophysics Data System (ADS)

Moualhi, Wafa; Ezzeddine, Zagrouba

2015-02-01

The motivation of this work is to register a tumor brain magnetic resonance (MR) image with a normal brain atlas. A normal brain atlas is deformed in order to take account of the presence of a large space occupying tumor. The method use a priori model of tumor growth assuming that the tumor grows in a radial way from a starting point. First, an affine transformation is used in order to bring the patient image and the brain atlas in a global correspondence. Second, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. Finally, the seeded atlas is deformed combining a method derived from optical flow principles and a model for tumor growth (MTG). Results show that an automatic segmentation method of brain structures in the presence of large deformation can be provided.

Encoding probabilistic brain atlases using Bayesian inference.

PubMed

Van Leemput, Koen

2009-06-01

This paper addresses the problem of creating probabilistic brain atlases from manually labeled training data. Probabilistic atlases are typically constructed by counting the relative frequency of occurrence of labels in corresponding locations across the training images. However, such an "averaging" approach generalizes poorly to unseen cases when the number of training images is limited, and provides no principled way of aligning the training datasets using deformable registration. In this paper, we generalize the generative image model implicitly underlying standard "average" atlases, using mesh-based representations endowed with an explicit deformation model. Bayesian inference is used to infer the optimal model parameters from the training data, leading to a simultaneous group-wise registration and atlas estimation scheme that encompasses standard averaging as a special case. We also use Bayesian inference to compare alternative atlas models in light of the training data, and show how this leads to a data compression problem that is intuitive to interpret and computationally feasible. Using this technique, we automatically determine the optimal amount of spatial blurring, the best deformation field flexibility, and the most compact mesh representation. We demonstrate, using 2-D training datasets, that the resulting models are better at capturing the structure in the training data than conventional probabilistic atlases. We also present experiments of the proposed atlas construction technique in 3-D, and show the resulting atlases' potential in fully-automated, pulse sequence-adaptive segmentation of 36 neuroanatomical structures in brain MRI scans.

Three-dimensional Talairach-Tournoux brain atlas

NASA Astrophysics Data System (ADS)

Fang, Anthony; Nowinski, Wieslaw L.; Nguyen, Bonnie T.; Bryan, R. Nick

1995-04-01

The Talairach-Tournoux Stereotaxic Atlas of the human brain is a frequently consulted resource in stereotaxic neurosurgery and computer-based neuroradiology. Its primary application lies in the 2-D analysis and interpretation of neurological images. However, for the purpose of the analysis and visualization of shapes and forms, accurate mensuration of volumes, or 3-D models matching, a 3-D representation of the atlas is essential. This paper proposes and describes, along with its difficulties, a 3-D geometric extension of the atlas. We introduce a `zero-potential' surface smoothing technique, along with a space-dependent convolution kernel and space-dependent normalization. The mesh-based atlas structures are hierarchically organized, and anatomically conform to the original atlas. Structures and their constituents can be independently selected and manipulated in real-time within an integrated system. The extended atlas may be navigated by itself, or interactively registered with patient data with the proportional grid system (piecewise linear) transformation. Visualization of the geometric atlas along with patient data gives a remarkable visual `feel' of the biological structures, not usually perceivable to the untrained eyes in conventional 2-D atlas to image analysis.

Toward the holistic, reference, and extendable atlas of the human brain, head, and neck.

PubMed

Nowinski, Wieslaw L

2015-06-01

Despite numerous efforts, a fairly complete (holistic) anatomical model of the whole, normal, adult human brain, which is required as the reference in brain studies and clinical applications, has not yet been constructed. Our ultimate objective is to build this kind of atlas from advanced in vivo imaging. This work presents the taxonomy of our currently developed brain atlases and addresses the design, content, functionality, and current results in the holistic atlas development as well as atlas usefulness and future directions. We have developed to date 35 commercial brain atlases (along with numerous research prototypes), licensed to 63 companies and institutions, and made available to medical societies, organizations, medical schools, and individuals. These atlases have been applied in education, research, and clinical applications. Hundreds of thousands of patients have been treated by using our atlases. Based on this experience, the first version of the holistic and reference atlas of the brain, head, and neck has been developed and made available. The atlas has been created from multispectral 3 and 7 Tesla and high-resolution CT in vivo scans. It is fully 3D, scalable, interactive, and highly detailed with about 3,000 labeled components. This atlas forms a foundation for the development of a multi-level molecular, cellular, anatomical, physiological, and behavioral brain atlas platform.

A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain

PubMed Central

Arganda-Carreras, Ignacio; Manoliu, Tudor; Mazuras, Nicolas; Schulze, Florian; Iglesias, Juan E.; Bühler, Katja; Jenett, Arnim; Rouyer, François; Andrey, Philippe

2018-01-01

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila, one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species. PMID:29628885

A Statistically Representative Atlas for Mapping Neuronal Circuits in the Drosophila Adult Brain.

PubMed

Arganda-Carreras, Ignacio; Manoliu, Tudor; Mazuras, Nicolas; Schulze, Florian; Iglesias, Juan E; Bühler, Katja; Jenett, Arnim; Rouyer, François; Andrey, Philippe

2018-01-01

Imaging the expression patterns of reporter constructs is a powerful tool to dissect the neuronal circuits of perception and behavior in the adult brain of Drosophila , one of the major models for studying brain functions. To date, several Drosophila brain templates and digital atlases have been built to automatically analyze and compare collections of expression pattern images. However, there has been no systematic comparison of performances between alternative atlasing strategies and registration algorithms. Here, we objectively evaluated the performance of different strategies for building adult Drosophila brain templates and atlases. In addition, we used state-of-the-art registration algorithms to generate a new group-wise inter-sex atlas. Our results highlight the benefit of statistical atlases over individual ones and show that the newly proposed inter-sex atlas outperformed existing solutions for automated registration and annotation of expression patterns. Over 3,000 images from the Janelia Farm FlyLight collection were registered using the proposed strategy. These registered expression patterns can be searched and compared with a new version of the BrainBaseWeb system and BrainGazer software. We illustrate the validity of our methodology and brain atlas with registration-based predictions of expression patterns in a subset of clock neurons. The described registration framework should benefit to brain studies in Drosophila and other insect species.

Automatic labeling of MR brain images through extensible learning and atlas forests.

PubMed

Xu, Lijun; Liu, Hong; Song, Enmin; Yan, Meng; Jin, Renchao; Hung, Chih-Cheng

2017-12-01

Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations. We propose an extensible learning model which allows the multiatlas-based framework capable of managing the datasets with numerous atlases or dynamic atlas datasets and simultaneously ensure the accuracy of automatic labeling. Two new strategies are used to reduce the time and space complexity and improve the efficiency of the automatic labeling of brain MR images. First, atlases are encoded to atlas forests through random forest technology to reduce the time consumed for cross-registration between atlases and target image, and a scatter spatial vector is designed to eliminate errors caused by inaccurate registration. Second, an atlas selection method based on the extensible learning model is used to select atlases for target image without traversing the entire dataset and then obtain the accurate labeling. The labeling results of the proposed method were evaluated in three public datasets, namely, IBSR, LONI LPBA40, and ADNI. With the proposed method, the dice coefficient metric values on the three datasets were 84.17 ± 4.61%, 83.25 ± 4.29%, and 81.88 ± 4.53% which were 5% higher than those of the conventional method, respectively. The efficiency of the extensible learning model was evaluated by state-of-the-art methods for labeling of MR brain images. Experimental results showed that the proposed method could achieve accurate labeling for MR brain images without traversing the entire datasets. In the proposed multiatlas-based method, extensible learning and atlas forests were applied to control the automatic labeling of brain anatomies on large atlas datasets or dynamic

The SRI24 multichannel brain atlas: construction and applications

NASA Astrophysics Data System (ADS)

Rohlfing, Torsten; Zahr, Natalie M.; Sullivan, Edith V.; Pfefferbaum, Adolf

2008-03-01

We present a new standard atlas of the human brain based on magnetic resonance images. The atlas was generated using unbiased population registration from high-resolution images obtained by multichannel-coil acquisition at 3T in a group of 24 normal subjects. The final atlas comprises three anatomical channels (T I-weighted, early and late spin echo), three diffusion-related channels (fractional anisotropy, mean diffusivity, diffusion-weighted image), and three tissue probability maps (CSF, gray matter, white matter). The atlas is dynamic in that it is implicitly represented by nonrigid transformations between the 24 subject images, as well as distortion-correction alignments between the image channels in each subject. The atlas can, therefore, be generated at essentially arbitrary image resolutions and orientations (e.g., AC/PC aligned), without compounding interpolation artifacts. We demonstrate in this paper two different applications of the atlas: (a) region definition by label propagation in a fiber tracking study is enabled by the increased sharpness of our atlas compared with other available atlases, and (b) spatial normalization is enabled by its average shape property. In summary, our atlas has unique features and will be made available to the scientific community as a resource and reference system for future imaging-based studies of the human brain.

Construction of brain atlases based on a multi-center MRI dataset of 2020 Chinese adults

PubMed Central

Liang, Peipeng; Shi, Lin; Chen, Nan; Luo, Yishan; Wang, Xing; Liu, Kai; Mok, Vincent CT; Chu, Winnie CW; Wang, Defeng; Li, Kuncheng

2015-01-01

Despite the known morphological differences (e.g., brain shape and size) in the brains of populations of different origins (e.g., age and race), the Chinese brain atlas is less studied. In the current study, we developed a statistical brain atlas based on a multi-center high quality magnetic resonance imaging (MRI) dataset of 2020 Chinese adults (18–76 years old). We constructed 12 Chinese brain atlas from the age 20 year to the age 75 at a 5 years interval. New Chinese brain standard space, coordinates, and brain area labels were further defined. The new Chinese brain atlas was validated in brain registration and segmentation. It was found that, as contrast to the MNI152 template, the proposed Chinese atlas showed higher accuracy in hippocampus segmentation and relatively smaller shape deformations during registration. These results indicate that a population-specific time varying brain atlas may be more appropriate for studies involving Chinese populations. PMID:26678304

High-resolution in vivo Wistar rodent brain atlas based on T1 weighted image

NASA Astrophysics Data System (ADS)

Huang, Su; Lu, Zhongkang; Huang, Weimin; Seramani, Sankar; Ramasamy, Boominathan; Sekar, Sakthivel; Guan, Cuntai; Bhakoo, Kishore

2016-03-01

Image based atlases for rats brain have a significant impact on pre-clinical research. In this project we acquired T1-weighted images from Wistar rodent brains with fine 59μm isotropical resolution for generation of the atlas template image. By applying post-process procedures using a semi-automatic brain extraction method, we delineated the brain tissues from source data. Furthermore, we applied a symmetric group-wise normalization method to generate an optimized template of T1 image of rodent brain, then aligned our template to the Waxholm Space. In addition, we defined several simple and explicit landmarks to corresponding our template with the well known Paxinos stereotaxic reference system. Anchoring at the origin of the Waxholm Space, we applied piece-wise linear transformation method to map the voxels of the template into the coordinates system in Paxinos' stereotoxic coordinates to facilitate the labelling task. We also cross-referenced our data with both published rodent brain atlas and image atlases available online, methodologically labelling the template to produce a Wistar brain atlas identifying more than 130 structures. Particular attention was paid to the cortex and cerebellum, as these areas encompass the most researched aspects of brain functions. Moreover, we adopted the structure hierarchy and naming nomenclature common to various atlases, so that the names and hierarchy structure presented in the atlas are readily recognised for easy use. It is believed the atlas will present a useful tool in rodent brain functional and pharmaceutical studies.

Effect of brain shift on the creation of functional atlases for deep brain stimulation surgery

PubMed Central

Pallavaram, Srivatsan; Remple, Michael S.; Neimat, Joseph S.; Kao, Chris; Konrad, Peter E.; D’Haese, Pierre-François

2011-01-01

Purpose In the recent past many groups have tried to build functional atlases of the deep brain using intra-operatively acquired information such as stimulation responses or micro-electrode recordings. An underlying assumption in building such atlases is that anatomical structures do not move between pre-operative imaging and intra-operative recording. In this study, we present evidences that this assumption is not valid. We quantify the effect of brain shift between pre-operative imaging and intra-operative recording on the creation of functional atlases using intra-operative somatotopy recordings and stimulation response data. Methods A total of 73 somatotopy points from 24 bilateral subthalamic nucleus (STN) implantations and 52 eye deviation stimulation response points from 17 bilateral STN implantations were used. These points were spatially normalized on a magnetic resonance imaging (MRI) atlas using a fully automatic non-rigid registration algorithm. Each implantation was categorized as having low, medium or large brain shift based on the amount of pneumocephalus visible on post-operative CT. The locations of somatotopy clusters and stimulation maps were analyzed for each category. Results The centroid of the large brain shift cluster of the somatotopy data (posterior, lateral, inferior: 3.06, 11.27, 5.36 mm) was found posterior, medial and inferior to that of the medium cluster (2.90, 13.57, 4.53 mm) which was posterior, medial and inferior to that of the low shift cluster (1.94, 13.92, 3.20 mm). The coordinates are referenced with respect to the mid-commissural point. Euclidean distances between the centroids were 1.68, 2.44 and 3.59 mm, respectively for low-medium, medium-large and low-large shift clusters. We found similar trends for the positions of the stimulation maps. The Euclidian distance between the highest probability locations on the low and medium-large shift maps was 4.06 mm. Conclusion The effect of brain shift in deep brain stimulation (DBS

Consistent cortical reconstruction and multi-atlas brain segmentation.

PubMed

Huo, Yuankai; Plassard, Andrew J; Carass, Aaron; Resnick, Susan M; Pham, Dzung L; Prince, Jerry L; Landman, Bennett A

2016-09-01

Whole brain segmentation and cortical surface reconstruction are two essential techniques for investigating the human brain. Spatial inconsistences, which can hinder further integrated analyses of brain structure, can result due to these two tasks typically being conducted independently of each other. FreeSurfer obtains self-consistent whole brain segmentations and cortical surfaces. It starts with subcortical segmentation, then carries out cortical surface reconstruction, and ends with cortical segmentation and labeling. However, this "segmentation to surface to parcellation" strategy has shown limitations in various cohorts such as older populations with large ventricles. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. A modification called MaCRUISE(+) is designed to perform well when white matter lesions are present. Comparing to the benchmarks CRUISE and FreeSurfer, the surface accuracy of MaCRUISE and MaCRUISE(+) is validated using two independent datasets with expertly placed cortical landmarks. A third independent dataset with expertly delineated volumetric labels is employed to compare segmentation performance. Finally, 200MR volumetric images from an older adult sample are used to assess the robustness of MaCRUISE and FreeSurfer. The advantages of MaCRUISE are: (1) MaCRUISE constructs self-consistent voxelwise segmentations and cortical surfaces, while MaCRUISE(+) is robust to white matter pathology. (2) MaCRUISE achieves more accurate whole brain segmentations than independently conducting the multi-atlas segmentation. (3) MaCRUISE is comparable in accuracy to FreeSurfer (when FreeSurfer does not exhibit global failures) while achieving greater robustness across an older adult population. MaCRUISE has been made freely

Brain iron homeostasis, the choroid plexus, and localization of iron transport proteins.

PubMed

Rouault, Tracey A; Zhang, De-Liang; Jeong, Suh Young

2009-12-01

Maintenance of appropriate iron homeostasis in the brain is important, but the mechanisms involved in brain iron uptake are incompletely understood. Here, we have analyzed where messenger RNAs that encode iron transport proteins are expressed in the brain, using the Allen Brain atlas, and we conclude that several important iron transporters are highly expressed in the choroid plexus. Based on recent estimates of the surface area of the choroid plexus and on MRI imaging studies of manganese uptake in the brain, we propose that the choroid plexus may have a much greater role than has been previously appreciated in brain iron transport.

An atlas of the prenatal mouse brain: gestational day 14.

PubMed

Schambra, U B; Silver, J; Lauder, J M

1991-11-01

A prenatal atlas of the mouse brain is presently unavailable and is needed for studies of normal and abnormal development, using techniques including immunocytochemistry and in situ hybridization. This atlas will be especially useful for researchers studying transgenic and mutant mice. This collection of photomicrographs and corresponding drawings of Gestational Day (GD) 14 mouse brain sections is an excerpt from a larger atlas encompassing GD 12-18. In composing this atlas, available published studies on the developing rodent brain were consulted to aid in the detailed labeling of embryonic brain structures. C57Bl/6J mice were mated for 1 h, and the presence of a copulation plug was designated as GD 0. GD 14 embryos were perfused transcardially with 4% paraformaldehyde in 0.1 M phosphate buffer and embedded in paraffin. Serial sections (10 microns thickness) were cut through whole heads in sagittal and horizontal planes. They were stained with hematoxylin and eosin and photographed. Magnifications were 43X and 31X for the horizontal and sagittal sections, respectively. Photographs were traced and line drawings prepared using an Adobe Illustrator on a Macintosh computer.

A 3D MRI-based atlas of a lizard brain.

PubMed

Hoops, Daniel; Desfilis, Ester; Ullmann, Jeremy F P; Janke, Andrew L; Stait-Gardner, Timothy; Devenyi, Gabriel A; Price, William S; Medina, Loreta; Whiting, Martin J; Keogh, J Scott

2018-06-22

Magnetic resonance imaging (MRI) is an established technique for neuroanatomical analysis, being particularly useful in the medical sciences. However, the application of MRI to evolutionary neuroscience is still in its infancy. Few magnetic resonance brain atlases exist outside the standard model organisms in neuroscience and no magnetic resonance atlas has been produced for any reptile brain. A detailed understanding of reptilian brain anatomy is necessary to elucidate the evolutionary origin of enigmatic brain structures such as the cerebral cortex. Here, we present a magnetic resonance atlas for the brain of a representative squamate reptile, the Australian tawny dragon (Agamidae: Ctenophorus decresii), which has been the object of numerous ecological and behavioral studies. We used a high-field 11.74T magnet, a paramagnetic contrasting-enhancing agent and minimum-deformation modeling of the brains of thirteen adult male individuals. From this, we created a high-resolution three-dimensional model of a lizard brain . The 3D-MRI model can be freely downloaded and allows a better comprehension of brain areas, nuclei, and fiber tracts, facilitating comparison with other species and setting the basis for future comparative evolution imaging studies. The MRI model of a tawny dragon brain (Ctenophorus decresii) can be viewed online and downloaded using the Wiley Biolucida Server at wiley.biolucida.net. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

A three-dimensional single-cell-resolution whole-brain atlas using CUBIC-X expansion microscopy and tissue clearing.

PubMed

Murakami, Tatsuya C; Mano, Tomoyuki; Saikawa, Shu; Horiguchi, Shuhei A; Shigeta, Daichi; Baba, Kousuke; Sekiya, Hiroshi; Shimizu, Yoshihiro; Tanaka, Kenji F; Kiyonari, Hiroshi; Iino, Masamitsu; Mochizuki, Hideki; Tainaka, Kazuki; Ueda, Hiroki R

2018-04-01

A three-dimensional single-cell-resolution mammalian brain atlas will accelerate systems-level identification and analysis of cellular circuits underlying various brain functions. However, its construction requires efficient subcellular-resolution imaging throughout the entire brain. To address this challenge, we developed a fluorescent-protein-compatible, whole-organ clearing and homogeneous expansion protocol based on an aqueous chemical solution (CUBIC-X). The expanded, well-cleared brain enabled us to construct a point-based mouse brain atlas with single-cell annotation (CUBIC-Atlas). CUBIC-Atlas reflects inhomogeneous whole-brain development, revealing a significant decrease in the cerebral visual and somatosensory cortical areas during postnatal development. Probabilistic activity mapping of pharmacologically stimulated Arc-dVenus reporter mouse brains onto CUBIC-Atlas revealed the existence of distinct functional structures in the hippocampal dentate gyrus. CUBIC-Atlas is shareable by an open-source web-based viewer, providing a new platform for whole-brain cell profiling.

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we

A three-dimensional histological atlas of the human basal ganglia. II. Atlas deformation strategy and evaluation in deep brain stimulation for Parkinson disease.

PubMed

Bardinet, Eric; Bhattacharjee, Manik; Dormont, Didier; Pidoux, Bernard; Malandain, Grégoire; Schüpbach, Michael; Ayache, Nicholas; Cornu, Philippe; Agid, Yves; Yelnik, Jérôme

2009-02-01

The localization of any given target in the brain has become a challenging issue because of the increased use of deep brain stimulation to treat Parkinson disease, dystonia, and nonmotor diseases (for example, Tourette syndrome, obsessive compulsive disorders, and depression). The aim of this study was to develop an automated method of adapting an atlas of the human basal ganglia to the brains of individual patients. Magnetic resonance images of the brain specimen were obtained before extraction from the skull and histological processing. Adaptation of the atlas to individual patient anatomy was performed by reshaping the atlas MR images to the images obtained in the individual patient using a hierarchical registration applied to a region of interest centered on the basal ganglia, and then applying the reshaping matrix to the atlas surfaces. Results were evaluated by direct visual inspection of the structures visible on MR images and atlas anatomy, by comparison with electrophysiological intraoperative data, and with previous atlas studies in patients with Parkinson disease. The method was both robust and accurate, never failing to provide an anatomically reliable atlas to patient registration. The registration obtained did not exceed a 1-mm mismatch with the electrophysiological signatures in the region of the subthalamic nucleus. This registration method applied to the basal ganglia atlas forms a powerful and reliable method for determining deep brain stimulation targets within the basal ganglia of individual patients.

A Four-Dimensional Probabilistic Atlas of the Human Brain

PubMed Central

Mazziotta, John; Toga, Arthur; Evans, Alan; Fox, Peter; Lancaster, Jack; Zilles, Karl; Woods, Roger; Paus, Tomas; Simpson, Gregory; Pike, Bruce; Holmes, Colin; Collins, Louis; Thompson, Paul; MacDonald, David; Iacoboni, Marco; Schormann, Thorsten; Amunts, Katrin; Palomero-Gallagher, Nicola; Geyer, Stefan; Parsons, Larry; Narr, Katherine; Kabani, Noor; Le Goualher, Georges; Feidler, Jordan; Smith, Kenneth; Boomsma, Dorret; Pol, Hilleke Hulshoff; Cannon, Tyrone; Kawashima, Ryuta; Mazoyer, Bernard

2001-01-01

The authors describe the development of a four-dimensional atlas and reference system that includes both macroscopic and microscopic information on structure and function of the human brain in persons between the ages of 18 and 90 years. Given the presumed large but previously unquantified degree of structural and functional variance among normal persons in the human population, the basis for this atlas and reference system is probabilistic. Through the efforts of the International Consortium for Brain Mapping (ICBM), 7,000 subjects will be included in the initial phase of database and atlas development. For each subject, detailed demographic, clinical, behavioral, and imaging information is being collected. In addition, 5,800 subjects will contribute DNA for the purpose of determining genotype– phenotype–behavioral correlations. The process of developing the strategies, algorithms, data collection methods, validation approaches, database structures, and distribution of results is described in this report. Examples of applications of the approach are described for the normal brain in both adults and children as well as in patients with schizophrenia. This project should provide new insights into the relationship between microscopic and macroscopic structure and function in the human brain and should have important implications in basic neuroscience, clinical diagnostics, and cerebral disorders. PMID:11522763

Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.

PubMed

Wu, Dan; Ma, Ting; Ceritoglu, Can; Li, Yue; Chotiyanonta, Jill; Hou, Zhipeng; Hsu, John; Xu, Xin; Brown, Timothy; Miller, Michael I; Mori, Susumu

2016-01-15

Technologies for multi-atlas brain segmentation of T1-weighted MRI images have rapidly progressed in recent years, with highly promising results. This approach, however, relies on a large number of atlases with accurate and consistent structural identifications. Here, we introduce our atlas inventories (n=90), which cover ages 4-82years with unique hierarchical structural definitions (286 structures at the finest level). This multi-atlas library resource provides the flexibility to choose appropriate atlases for various studies with different age ranges and structure-definition criteria. In this paper, we describe the details of the atlas resources and demonstrate the improved accuracy achievable with a dynamic age-matching approach, in which atlases that most closely match the subject's age are dynamically selected. The advanced atlas creation strategy, together with atlas pre-selection principles, is expected to support the further development of multi-atlas image segmentation. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of representative magnetic resonance imaging-based atlases of the canine brain and evaluation of three methods for atlas-based segmentation.

PubMed

Milne, Marjorie E; Steward, Christopher; Firestone, Simon M; Long, Sam N; O'Brien, Terrence J; Moffat, Bradford A

2016-04-01

To develop representative MRI atlases of the canine brain and to evaluate 3 methods of atlas-based segmentation (ABS). 62 dogs without clinical signs of epilepsy and without MRI evidence of structural brain disease. The MRI scans from 44 dogs were used to develop 4 templates on the basis of brain shape (brachycephalic, mesaticephalic, dolichocephalic, and combined mesaticephalic and dolichocephalic). Atlas labels were generated by segmenting the brain, ventricular system, hippocampal formation, and caudate nuclei. The MRI scans from the remaining 18 dogs were used to evaluate 3 methods of ABS (manual brain extraction and application of a brain shape-specific template [A], automatic brain extraction and application of a brain shape-specific template [B], and manual brain extraction and application of a combined template [C]). The performance of each ABS method was compared by calculation of the Dice and Jaccard coefficients, with manual segmentation used as the gold standard. Method A had the highest mean Jaccard coefficient and was the most accurate ABS method assessed. Measures of overlap for ABS methods that used manual brain extraction (A and C) ranged from 0.75 to 0.95 and compared favorably with repeated measures of overlap for manual extraction, which ranged from 0.88 to 0.97. Atlas-based segmentation was an accurate and repeatable method for segmentation of canine brain structures. It could be performed more rapidly than manual segmentation, which should allow the application of computer-assisted volumetry to large data sets and clinical cases and facilitate neuroimaging research and disease diagnosis.

Automatic Structural Parcellation of Mouse Brain MRI Using Multi-Atlas Label Fusion

PubMed Central

Ma, Da; Cardoso, Manuel J.; Modat, Marc; Powell, Nick; Wells, Jack; Holmes, Holly; Wiseman, Frances; Tybulewicz, Victor; Fisher, Elizabeth; Lythgoe, Mark F.; Ourselin, Sébastien

2014-01-01

Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art methodology for automatic parcellation of structural images. However, few studies have applied these methods to preclinical research. In this study, we present a fully automatic framework for mouse brain MRI structural parcellation using multi-atlas segmentation propagation. The framework adopts the similarity and truth estimation for propagated segmentations (STEPS) algorithm, which utilises a locally normalised cross correlation similarity metric for atlas selection and an extended simultaneous truth and performance level estimation (STAPLE) framework for multi-label fusion. The segmentation accuracy of the multi-atlas framework was evaluated using publicly available mouse brain atlas databases with pre-segmented manually labelled anatomical structures as the gold standard, and optimised parameters were obtained for the STEPS algorithm in the label fusion to achieve the best segmentation accuracy. We showed that our multi-atlas framework resulted in significantly higher segmentation accuracy compared to single-atlas based segmentation, as well as to the original STAPLE framework. PMID:24475148

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

PubMed Central

Wang, Jiahui; Vachet, Clement; Rumple, Ashley; Gouttard, Sylvain; Ouziel, Clémentine; Perrot, Emilie; Du, Guangwei; Huang, Xuemei; Gerig, Guido; Styner, Martin

2014-01-01

Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual “atlases” that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

PubMed

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

PubMed

Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

2015-09-01

Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

Integrating Retraction Modeling Into an Atlas-Based Framework for Brain Shift Prediction

PubMed Central

Chen, Ishita; Ong, Rowena E.; Simpson, Amber L.; Sun, Kay; Thompson, Reid C.

2015-01-01

In recent work, an atlas-based statistical model for brain shift prediction, which accounts for uncertainty in the intraoperative environment, has been proposed. Previous work reported in the literature using this technique did not account for local deformation caused by surgical retraction. It is challenging to precisely localize the retractor location prior to surgery and the retractor is often moved in the course of the procedure. This paper proposes a technique that involves computing the retractor-induced brain deformation in the operating room through an active model solve and linearly superposing the solution with the precomputed deformation atlas. As a result, the new method takes advantage of the atlas-based framework’s accounting for uncertainties while also incorporating the effects of retraction with minimal intraoperative computing. This new approach was tested using simulation and phantom experiments. The results showed an improvement in average shift correction from 50% (ranging from 14 to 81%) for gravity atlas alone to 80% using the active solve retraction component (ranging from 73 to 85%). This paper presents a novel yet simple way to integrate retraction into the atlas-based brain shift computation framework. PMID:23864146

Structural Brain Atlases: Design, Rationale, and Applications in Normal and Pathological Cohorts

PubMed Central

Mandal, Pravat K.; Mahajan, Rashima; Dinov, Ivo D.

2015-01-01

Structural magnetic resonance imaging (MRI) provides anatomical information about the brain in healthy as well as in diseased conditions. On the other hand, functional MRI (fMRI) provides information on the brain activity during performance of a specific task. Analysis of fMRI data requires the registration of the data to a reference brain template in order to identify the activated brain regions. Brain templates also find application in other neuroimaging modalities, such as diffusion tensor imaging and multi-voxel spectroscopy. Further, there are certain differences (e.g., brain shape and size) in the brains of populations of different origin and during diseased conditions like in Alzheimer’s disease (AD), population and disease-specific brain templates may be considered crucial for accurate registration and subsequent analysis of fMRI as well as other neuroimaging data. This manuscript provides a comprehensive review of the history, construction and application of brain atlases. A chronological outline of the development of brain template design, starting from the Talairach and Tournoux atlas to the Chinese brain template (to date), along with their respective detailed construction protocols provides the backdrop to this manuscript. The manuscript also provides the automated workflow-based protocol for designing a population-specific brain atlas from structural MRI data using LONI Pipeline graphical workflow environment. We conclude by discussing the scope of brain templates as a research tool and their application in various neuroimaging modalities. PMID:22647262

Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

2009-02-01

Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

Monitoring the injured brain: registered, patient specific atlas models to improve accuracy of recovered brain saturation values

NASA Astrophysics Data System (ADS)

Clancy, Michael; Belli, Antonio; Davies, David; Lucas, Samuel J. E.; Su, Zhangjie; Dehghani, Hamid

2015-07-01

The subject of superficial contamination and signal origins remains a widely debated topic in the field of Near Infrared Spectroscopy (NIRS), yet the concept of using the technology to monitor an injured brain, in a clinical setting, poses additional challenges concerning the quantitative accuracy of recovered parameters. Using high density diffuse optical tomography probes, quantitatively accurate parameters from different layers (skin, bone and brain) can be recovered from subject specific reconstruction models. This study assesses the use of registered atlas models for situations where subject specific models are not available. Data simulated from subject specific models were reconstructed using the 8 registered atlas models implementing a regional (layered) parameter recovery in NIRFAST. A 3-region recovery based on the atlas model yielded recovered brain saturation values which were accurate to within 4.6% (percentage error) of the simulated values, validating the technique. The recovered saturations in the superficial regions were not quantitatively accurate. These findings highlight differences in superficial (skin and bone) layer thickness between the subject and atlas models. This layer thickness mismatch was propagated through the reconstruction process decreasing the parameter accuracy.

Windows on the brain: the emerging role of atlases and databases in neuroscience

NASA Technical Reports Server (NTRS)

Van Essen, David C.; VanEssen, D. C. (Principal Investigator)

2002-01-01

Brain atlases and associated databases have great potential as gateways for navigating, accessing, and visualizing a wide range of neuroscientific data. Recent progress towards realizing this potential includes the establishment of probabilistic atlases, surface-based atlases and associated databases, combined with improvements in visualization capabilities and internet access.

Recent Science Highlights of the Van Allen Probes Mission

NASA Astrophysics Data System (ADS)

Ukhorskiy, Aleksandr

2016-10-01

The morning of 30 August 2012 saw an Atlas 5 rocket launch NASA's second Living With a Star spacecraft mission, the twin Radiation Belt Storm Probes, into an elliptic orbit cutting through Earth's radiation belts. Renamed the Van Allen Probes soon after launch, the Probes are designed to determine how the highly variable populations of high-energy charged particles within the radiation belts, dangerous to astronauts and satellites, are created, respond to solar variations, and evolve in space environments. The Van Allen Probes mission extends beyond the practical considerations of the hazard's of Earth's space environment. Twentieth century observations of space and astrophysical systems throughout the solar system and out into the observable universe have shown that the processes that generate intense particle radiation within magnetized environments such as Earth's are universal. During its mission the Van Allen Probes verified and quantified previously suggested energization processes, discovered new energization mechanisms, revealed the critical importance of dynamic plasma injections into the innermost magnetosphere, and used uniquely capable instruments to reveal inner radiation belt features that were all but invisible to previous sensors. This paper gives a brief overview of the mission, presents some recent science highlights, and discusses plans for the extended mission.

A combined histological and MRI brain atlas of the common marmoset monkey, Callithrix jacchus.

PubMed

Newman, John D; Kenkel, William M; Aronoff, Emily C; Bock, Nicholas A; Zametkin, Molly R; Silva, Afonso C

2009-12-11

The common marmoset, Callithrix jacchus, is of growing importance for research in neuroscience and related fields. In the present work, we describe a combined histological and magnetic resonance imaging (MRI) atlas constructed from the brains of two adult female marmosets. Histological sections were processed from Nissl staining and digitized to produce an atlas in a large format that facilitates visualization of structures with significant detail. Naming of identifiable brain structures was performed utilizing current terminology. The histological sections and a simplified schematic atlas are available online at http://udn.nichd.nih.gov/brainatlas_home.html.

A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei

PubMed Central

Pauli, Wolfgang M.; Nili, Amanda N.; Tyszka, J. Michael

2018-01-01

Recent advances in magnetic resonance imaging methods, including data acquisition, pre-processing and analysis, have benefited research on the contributions of subcortical brain nuclei to human cognition and behavior. At the same time, these developments have led to an increasing need for a high-resolution probabilistic in vivo anatomical atlas of subcortical nuclei. In order to address this need, we constructed high spatial resolution, three-dimensional templates, using high-accuracy diffeomorphic registration of T1- and T2- weighted structural images from 168 typical adults between 22 and 35 years old. In these templates, many tissue boundaries are clearly visible, which would otherwise be impossible to delineate in data from individual studies. The resulting delineations of subcortical nuclei complement current histology-based atlases. We further created a companion library of software tools for atlas development, to offer an open and evolving resource for the creation of a crowd-sourced in vivo probabilistic anatomical atlas of the human brain. PMID:29664465

Allen Brain Atlas-Driven Visualizations: A Web-Based Gene Expression Energy Visualization Tool

DTIC Science & Technology

2014-05-21

purposes notwithstanding any copyright anno - tation thereon. The views and conclusions contained herein are those of the authors and should not be...Brain Res. Brain Res. Rev. 28, 309–369. doi: 10.1016/S0165-0173(98)00019-8 Bostock, M., Ogievetsky, V., and Heer, J . (2011). D³ data-driven documents...omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207–210. doi: 10.1093/nar/30.1.207 Eppig, J . T., Blake

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

PubMed Central

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-01-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

PubMed

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases

PubMed Central

Forbes, Jessica L.; Kim, Regina E. Y.; Paulsen, Jane S.; Johnson, Hans J.

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%. PMID:27536233

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases.

PubMed

Forbes, Jessica L; Kim, Regina E Y; Paulsen, Jane S; Johnson, Hans J

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%.

A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain

PubMed Central

Baumann, Cédric; Zouaoui, Sonia; Yordanova, Yordanka; Blonski, Marie; Rigau, Valérie; Chemouny, Stéphane; Taillandier, Luc; Bauchet, Luc; Duffau, Hugues; Paragios, Nikos

2016-01-01

Diffuse WHO grade II gliomas are diffusively infiltrative brain tumors characterized by an unavoidable anaplastic transformation. Their management is strongly dependent on their location in the brain due to interactions with functional regions and potential differences in molecular biology. In this paper, we present the construction of a probabilistic atlas mapping the preferential locations of diffuse WHO grade II gliomas in the brain. This is carried out through a sparse graph whose nodes correspond to clusters of tumors clustered together based on their spatial proximity. The interest of such an atlas is illustrated via two applications. The first one correlates tumor location with the patient’s age via a statistical analysis, highlighting the interest of the atlas for studying the origins and behavior of the tumors. The second exploits the fact that the tumors have preferential locations for automatic segmentation. Through a coupled decomposed Markov Random Field model, the atlas guides the segmentation process, and characterizes which preferential location the tumor belongs to and consequently which behavior it could be associated to. Leave-one-out cross validation experiments on a large database highlight the robustness of the graph, and yield promising segmentation results. PMID:26751577

Whole-brain activity mapping onto a zebrafish brain atlas.

PubMed

Randlett, Owen; Wee, Caroline L; Naumann, Eva A; Nnaemeka, Onyeka; Schoppik, David; Fitzgerald, James E; Portugues, Ruben; Lacoste, Alix M B; Riegler, Clemens; Engert, Florian; Schier, Alexander F

2015-11-01

In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open-source atlas containing molecular labels and definitions of anatomical regions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated extracellular signal–regulated kinase (ERK) as a readout of neural activity, we have developed a system to create and contextualize whole-brain maps of stimulus- and behavior-dependent neural activity. This mitogen-activated protein kinase (MAP)-mapping assay is technically simple, and data analysis is completely automated. Because MAP-mapping is performed on freely swimming fish, it is applicable to studies of nearly any stimulus or behavior. Here we demonstrate our high-throughput approach using pharmacological, visual and noxious stimuli, as well as hunting and feeding. The resultant maps outline hundreds of areas associated with behaviors.

Whole-brain activity mapping onto a zebrafish brain atlas

PubMed Central

Randlett, Owen; Wee, Caroline L.; Naumann, Eva A.; Nnaemeka, Onyeka; Schoppik, David; Fitzgerald, James E.; Portugues, Ruben; Lacoste, Alix M.B.; Riegler, Clemens; Engert, Florian; Schier, Alexander F.

2015-01-01

In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open source atlas containing molecular labels and anatomical region definitions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated-Extracellular signal-regulated kinase (ERK/MAPK) as a readout of neural activity, we have developed a system to create and contextualize whole brain maps of stimulus- and behavior-dependent neural activity. This MAP-Mapping (Mitogen Activated Protein kinase – Mapping) assay is technically simple, fast, inexpensive, and data analysis is completely automated. Since MAP-Mapping is performed on fish that are freely swimming, it is applicable to nearly any stimulus or behavior. We demonstrate the utility of our high-throughput approach using hunting/feeding, pharmacological, visual and noxious stimuli. The resultant maps outline hundreds of areas associated with behaviors. PMID:26778924

Geometry Processing of Conventionally Produced Mouse Brain Slice Images.

PubMed

Agarwal, Nitin; Xu, Xiangmin; Gopi, M

2018-04-21

Brain mapping research in most neuroanatomical laboratories relies on conventional processing techniques, which often introduce histological artifacts such as tissue tears and tissue loss. In this paper we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space. This is achieved first by constructing a virtual 3D mouse brain model from annotated slices of Allen Reference Atlas (ARA). Virtual re-slicing of the reconstructed model generates ARA-based slice images corresponding to the microscopic images of histological brain sections. These image pairs are aligned using a geometric approach through contour images. Histological artifacts in the microscopic images are detected and removed using Constrained Delaunay Triangulation before performing global alignment. Finally, non-linear registration is performed by solving Laplace's equation with Dirichlet boundary conditions. Our methods provide significant improvements over previously reported registration techniques for the tested slices in 3D space, especially on slices with significant histological artifacts. Further, as one of the application we count the number of neurons in various anatomical regions using a dataset of 51 microscopic slices from a single mouse brain. To the best of our knowledge the presented work is the first that automatically registers both clean as well as highly damaged high-resolutions histological slices of mouse brain to a 3D annotated reference atlas space. This work represents a significant contribution to this subfield of neuroscience as it provides tools to neuroanatomist for analyzing and processing histological data. Copyright © 2018 Elsevier B.V. All rights reserved.

Altered voxel-wise gray matter structural brain networks in schizophrenia: Association with brain genetic expression pattern.

PubMed

Liu, Feng; Tian, Hongjun; Li, Jie; Li, Shen; Zhuo, Chuanjun

2018-05-04

Previous seed- and atlas-based structural covariance/connectivity analyses have demonstrated that patients with schizophrenia is accompanied by aberrant structural connection and abnormal topological organization. However, it remains unclear whether this disruption is present in unbiased whole-brain voxel-wise structural covariance networks (SCNs) and whether brain genetic expression variations are linked with network alterations. In this study, ninety-five patients with schizophrenia and 95 matched healthy controls were recruited and gray matter volumes were extracted from high-resolution structural magnetic resonance imaging scans. Whole-brain voxel-wise gray matter SCNs were constructed at the group level and were further analyzed by using graph theory method. Nonparametric permutation tests were employed for group comparisons. In addition, regression modes along with random effect analysis were utilized to explore the associations between structural network changes and gene expression from the Allen Human Brain Atlas. Compared with healthy controls, the patients with schizophrenia showed significantly increased structural covariance strength (SCS) in the right orbital part of superior frontal gyrus and bilateral middle frontal gyrus, while decreased SCS in the bilateral superior temporal gyrus and precuneus. The altered SCS showed reproducible correlations with the expression profiles of the gene classes involved in therapeutic targets and neurodevelopment. Overall, our findings not only demonstrate that the topological architecture of whole-brain voxel-wise SCNs is impaired in schizophrenia, but also provide evidence for the possible role of therapeutic targets and neurodevelopment-related genes in gray matter structural brain networks in schizophrenia.

Parcellation of the Healthy Neonatal Brain into 107 Regions Using Atlas Propagation through Intermediate Time Points in Childhood.

PubMed

Blesa, Manuel; Serag, Ahmed; Wilkinson, Alastair G; Anblagan, Devasuda; Telford, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Macnaught, Gillian; Semple, Scott I; Bastin, Mark E; Boardman, James P

2016-01-01

Neuroimage analysis pipelines rely on parcellated atlases generated from healthy individuals to provide anatomic context to structural and diffusion MRI data. Atlases constructed using adult data introduce bias into studies of early brain development. We aimed to create a neonatal brain atlas of healthy subjects that can be applied to multi-modal MRI data. Structural and diffusion 3T MRI scans were acquired soon after birth from 33 typically developing neonates born at term (mean postmenstrual age at birth 39(+5) weeks, range 37(+2)-41(+6)). An adult brain atlas (SRI24/TZO) was propagated to the neonatal data using temporal registration via childhood templates with dense temporal samples (NIH Pediatric Database), with the final atlas (Edinburgh Neonatal Atlas, ENA33) constructed using the Symmetric Group Normalization (SyGN) method. After this step, the computed final transformations were applied to T2-weighted data, and fractional anisotropy, mean diffusivity, and tissue segmentations to provide a multi-modal atlas with 107 anatomical regions; a symmetric version was also created to facilitate studies of laterality. Volumes of each region of interest were measured to provide reference data from normal subjects. Because this atlas is generated from step-wise propagation of adult labels through intermediate time points in childhood, it may serve as a useful starting point for modeling brain growth during development.

Warping of a computerized 3-D atlas to match brain image volumes for quantitative neuroanatomical and functional analysis

NASA Astrophysics Data System (ADS)

Evans, Alan C.; Dai, Weiqian; Collins, D. Louis; Neelin, Peter; Marrett, Sean

1991-06-01

We describe the implementation, experience and preliminary results obtained with a 3-D computerized brain atlas for topographical and functional analysis of brain sub-regions. A volume-of-interest (VOI) atlas was produced by manual contouring on 64 adjacent 2 mm-thick MRI slices to yield 60 brain structures in each hemisphere which could be adjusted, originally by global affine transformation or local interactive adjustments, to match individual MRI datasets. We have now added a non-linear deformation (warp) capability (Bookstein, 1989) into the procedure for fitting the atlas to the brain data. Specific target points are identified in both atlas and MRI spaces which define a continuous 3-D warp transformation that maps the atlas on to the individual brain image. The procedure was used to fit MRI brain image volumes from 16 young normal volunteers. Regional volume and positional variability were determined, the latter in such a way as to assess the extent to which previous linear models of brain anatomical variability fail to account for the true variation among normal individuals. Using a linear model for atlas deformation yielded 3-D fits of the MRI data which, when pooled across subjects and brain regions, left a residual mis-match of 6 - 7 mm as compared to the non-linear model. The results indicate a substantial component of morphometric variability is not accounted for by linear scaling. This has profound implications for applications which employ stereotactic coordinate systems which map individual brains into a common reference frame: quantitative neuroradiology, stereotactic neurosurgery and cognitive mapping of normal brain function with PET. In the latter case, the combination of a non-linear deformation algorithm would allow for accurate measurement of individual anatomic variations and the inclusion of such variations in inter-subject averaging methodologies used for cognitive mapping with PET.

Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping.

PubMed

Zhang, Yuyao; Wei, Hongjiang; Cronin, Matthew J; He, Naying; Yan, Fuhua; Liu, Chunlei

2018-05-01

Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2-weighted MRI. A 4D developmental quantitative susceptibility mapping (QSM) atlas may facilitate the estimation of age-related iron changes in deep gray matter nuclei and myelin changes in white matter. To this end, group-wise co-registered QSM templates were generated over various age intervals from age 1-83 years old. Registration was achieved by combining both T1-weighted and QSM images. Based on the proposed template, we created an accurate deep gray matter nuclei parcellation map (DGM map). Notably, we segmented thalamus into 5 sub-regions, i.e. the anterior nuclei, the median nuclei, the lateral nuclei, the pulvinar and the internal medullary lamina. Furthermore, we built a "whole brain QSM parcellation map" by combining existing cortical parcellation and white-matter atlases with the proposed DGM map. Based on the proposed QSM atlas, the segmentation accuracy of iron-rich nuclei using QSM is significantly improved, especially for children and adolescent subjects. The age-related progression of magnetic susceptibility in each of the deep gray matter nuclei, the hippocampus, and the amygdala was estimated. Our automated atlas-based analysis provided a systematic confirmation of previous findings on susceptibility progression with age resulting from manual ROI drawings in deep gray matter nuclei. The susceptibility development in the hippocampus and the amygdala follow an iron accumulation model; while in the thalamus sub-regions, the susceptibility development exhibits a variety of trends. It is envisioned that the newly developed 4D QSM atlas will serve as a template for studying brain iron deposition and myelination/demyelination in both normal aging and various brain diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with

Multi-object model-based multi-atlas segmentation for rodent brains using dense discrete correspondences

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Kim, Sun Hyung; Styner, Martin

2016-03-01

The delineation of rodent brain structures is challenging due to low-contrast multiple cortical and subcortical organs that are closely interfacing to each other. Atlas-based segmentation has been widely employed due to its ability to delineate multiple organs at the same time via image registration. The use of multiple atlases and subsequent label fusion techniques has further improved the robustness and accuracy of atlas-based segmentation. However, the accuracy of atlas-based segmentation is still prone to registration errors; for example, the segmentation of in vivo MR images can be less accurate and robust against image artifacts than the segmentation of post mortem images. In order to improve the accuracy and robustness of atlas-based segmentation, we propose a multi-object, model-based, multi-atlas segmentation method. We first establish spatial correspondences across atlases using a set of dense pseudo-landmark particles. We build a multi-object point distribution model using those particles in order to capture inter- and intra- subject variation among brain structures. The segmentation is obtained by fitting the model into a subject image, followed by label fusion process. Our result shows that the proposed method resulted in greater accuracy than comparable segmentation methods, including a widely used ANTs registration tool.

Screw-Retaining Allen Wrench

NASA Technical Reports Server (NTRS)

Granett, D.

1985-01-01

Steadying screws with fingers unnecessary. Crimp in uncompressed spring wire slightly protrudes from one facet of Allen wrench. Compressed spring retains Allen screw. Tool used with Allen-head screws in cramped spaces with little or no room for fingers to hold fastener while turned by wrench.

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of

A brain MRI atlas of the common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.

2014-03-01

The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.

The informatics of a C57BL/6J mouse brain atlas.

PubMed

MacKenzie-Graham, Allan; Jones, Eagle S; Shattuck, David W; Dinov, Ivo D; Bota, Mihail; Toga, Arthur W

2003-01-01

The Mouse Atlas Project (MAP) aims to produce a framework for organizing and analyzing the large volumes of neuroscientific data produced by the proliferation of genetically modified animals. Atlases provide an invaluable aid in understanding the impact of genetic manipulations by providing a standard for comparison. We use a digital atlas as the hub of an informatics network, correlating imaging data, such as structural imaging and histology, with text-based data, such as nomenclature, connections, and references. We generated brain volumes using magnetic resonance microscopy (MRM), classical histology, and immunohistochemistry, and registered them into a common and defined coordinate system. Specially designed viewers were developed in order to visualize multiple datasets simultaneously and to coordinate between textual and image data. Researchers can navigate through the brain interchangeably, in either a text-based or image-based representation that automatically updates information as they move. The atlas also allows the independent entry of other types of data, the facile retrieval of information, and the straight-forward display of images. In conjunction with centralized servers, image and text data can be kept current and can decrease the burden on individual researchers' computers. A comprehensive framework that encompasses many forms of information in the context of anatomic imaging holds tremendous promise for producing new insights. The atlas and associated tools can be found at http://www.loni.ucla.edu/MAP.

Large-scale extraction of brain connectivity from the neuroscientific literature

PubMed Central

Richardet, Renaud; Chappelier, Jean-Cédric; Telefont, Martin; Hill, Sean

2015-01-01

Motivation: In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications. This lack of normalization and centralization hinders the large-scale integration of brain connectivity results. In this article, we present text-mining models to extract and aggregate brain connectivity results from 13.2 million PubMed abstracts and 630 216 full-text publications related to neuroscience. The brain regions are identified with three different named entity recognizers (NERs) and then normalized against two atlases: the Allen Brain Atlas (ABA) and the atlas from the Brain Architecture Management System (BAMS). We then use three different extractors to assess inter-region connectivity. Results: NERs and connectivity extractors are evaluated against a manually annotated corpus. The complete in litero extraction models are also evaluated against in vivo connectivity data from ABA with an estimated precision of 78%. The resulting database contains over 4 million brain region mentions and over 100 000 (ABA) and 122 000 (BAMS) potential brain region connections. This database drastically accelerates connectivity literature review, by providing a centralized repository of connectivity data to neuroscientists. Availability and implementation: The resulting models are publicly available at github.com/BlueBrain/bluima. Contact: renaud.richardet@epfl.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25609795

Computation of a high-resolution MRI 3D stereotaxic atlas of the sheep brain.

PubMed

Ella, Arsène; Delgadillo, José A; Chemineau, Philippe; Keller, Matthieu

2017-02-15

The sheep model was first used in the fields of animal reproduction and veterinary sciences and then was utilized in fundamental and preclinical studies. For more than a decade, magnetic resonance (MR) studies performed on this model have been increasingly reported, especially in the field of neuroscience. To contribute to MR translational neuroscience research, a brain template and an atlas are necessary. We have recently generated the first complete T1-weighted (T1W) and T2W MR population average images (or templates) of in vivo sheep brains. In this study, we 1) defined a 3D stereotaxic coordinate system for previously established in vivo population average templates; 2) used deformation fields obtained during optimized nonlinear registrations to compute nonlinear tissues or prior probability maps (nlTPMs) of cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) tissues; 3) delineated 25 external and 28 internal sheep brain structures by segmenting both templates and nlTPMs; and 4) annotated and labeled these structures using an existing histological atlas. We built a quality high-resolution 3D atlas of average in vivo sheep brains linked to a reference stereotaxic space. The atlas and nlTPMs, associated with previously computed T1W and T2W in vivo sheep brain templates and nlTPMs, provide a complete set of imaging space that are able to be imported into other imaging software programs and could be used as standardized tools for neuroimaging studies or other neuroscience methods, such as image registration, image segmentation, identification of brain structures, implementation of recording devices, or neuronavigation. J. Comp. Neurol. 525:676-692, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow.

PubMed

Stockton, David B; Santamaria, Fidel

2017-10-01

We developed software tools to download, extract features, and organize the Cell Types Database from the Allen Brain Institute (ABI) in order to integrate its whole cell patch clamp characterization data into the automated modeling/data analysis cycle. To expand the potential user base we employed both Python and MATLAB. The basic set of tools downloads selected raw data and extracts cell, sweep, and spike features, using ABI's feature extraction code. To facilitate data manipulation we added a tool to build a local specialized database of raw data plus extracted features. Finally, to maximize automation, we extended our NeuroManager workflow automation suite to include these tools plus a separate investigation database. The extended suite allows the user to integrate ABI experimental and modeling data into an automated workflow deployed on heterogeneous computer infrastructures, from local servers, to high performance computing environments, to the cloud. Since our approach is focused on workflow procedures our tools can be modified to interact with the increasing number of neuroscience databases being developed to cover all scales and properties of the nervous system.

Rat brain digital stereotaxic white matter atlas with fine tract delineation in Paxinos space and its automated applications in DTI data analysis.

PubMed

Liang, Shengxiang; Wu, Shang; Huang, Qi; Duan, Shaofeng; Liu, Hua; Li, Yuxiao; Zhao, Shujun; Nie, Binbin; Shan, Baoci

2017-11-01

To automatically analyze diffusion tensor images of the rat brain via both voxel-based and ROI-based approaches, we constructed a new white matter atlas of the rat brain with fine tracts delineation in the Paxinos and Watson space. Unlike in previous studies, we constructed a digital atlas image from the latest edition of the Paxinos and Watson. This atlas contains 111 carefully delineated white matter fibers. A white matter network of rat brain based on anatomy was constructed by locating the intersection of all these tracts and recording the nuclei on the pathway of each white matter tract. Moreover, a compatible rat brain template from DTI images was created and standardized into the atlas space. To evaluate the automated application of the atlas in DTI data analysis, a group of rats with right-side middle cerebral artery occlusion (MCAO) and those without were enrolled in this study. The voxel-based analysis result shows that the brain region showing significant declines in signal in the MCAO rats was consistent with the occlusion position. We constructed a stereotaxic white matter atlas of the rat brain with fine tract delineation and a compatible template for the data analysis of DTI images of the rat brain. Copyright © 2017 Elsevier Inc. All rights reserved.

Three-dimensional stereotactic atlas of the adult human skull correlated with the brain, cranial nerves, and intracranial vasculature.

PubMed

Nowinski, Wieslaw L; Thaung, Thant Shoon Let; Chua, Beng Choon; Yi, Su Hnin Wut; Ngai, Vincent; Yang, Yili; Chrzan, Robert; Urbanik, Andrzej

2015-05-15

Although the adult human skull is a complex and multifunctional structure, its 3D, complete, realistic, and stereotactic atlas has not yet been created. This work addresses the construction of a 3D interactive atlas of the adult human skull spatially correlated with the brain, cranial nerves, and intracranial vasculature. The process of atlas construction included computed tomography (CT) high-resolution scan acquisition, skull extraction, skull parcellation, 3D disarticulated bone surface modeling, 3D model simplification, brain-skull registration, 3D surface editing, 3D surface naming and color-coding, integration of the CT-derived 3D bony models with the existing brain atlas, and validation. The virtual skull model created is complete with all 29 bones, including the auditory ossicles (being among the smallest bones). It contains all typical bony features and landmarks. The created skull model is superior to the existing skull models in terms of completeness, realism, and integration with the brain along with blood vessels and cranial nerves. This skull atlas is valuable for medical students and residents to easily get familiarized with the skull and surrounding anatomy with a few clicks. The atlas is also useful for educators to prepare teaching materials. It may potentially serve as a reference aid in the reading and operating rooms. Copyright © 2015 Elsevier B.V. All rights reserved.

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data

PubMed Central

James, G. Andrew; Hazaroglu, Onder; Bush, Keith A.

2015-01-01

The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI’s translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants’ functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group’s mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI= 0.72–0.85) than with the Random atlases (JI=0.59–0.63; all p<0.001 after Bonferroni correction). Task and Rest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data.

PubMed

James, George Andrew; Hazaroglu, Onder; Bush, Keith A

2016-02-01

The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI's translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants' functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group's mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI=0.72-0.85) than with the Random atlases (JI=0.59-0.63; all p<0.001 after Bonferroni correction). Task and Rest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

Multi-atlas attenuation correction supports full quantification of static and dynamic brain PET data in PET-MR

NASA Astrophysics Data System (ADS)

Mérida, Inés; Reilhac, Anthonin; Redouté, Jérôme; Heckemann, Rolf A.; Costes, Nicolas; Hammers, Alexander

2017-04-01

In simultaneous PET-MR, attenuation maps are not directly available. Essential for absolute radioactivity quantification, they need to be derived from MR or PET data to correct for gamma photon attenuation by the imaged object. We evaluate a multi-atlas attenuation correction method for brain imaging (MaxProb) on static [18F]FDG PET and, for the first time, on dynamic PET, using the serotoninergic tracer [18F]MPPF. A database of 40 MR/CT image pairs (atlases) was used. The MaxProb method synthesises subject-specific pseudo-CTs by registering each atlas to the target subject space. Atlas CT intensities are then fused via label propagation and majority voting. Here, we compared these pseudo-CTs with the real CTs in a leave-one-out design, contrasting the MaxProb approach with a simplified single-atlas method (SingleAtlas). We evaluated the impact of pseudo-CT accuracy on reconstructed PET images, compared to PET data reconstructed with real CT, at the regional and voxel levels for the following: radioactivity images; time-activity curves; and kinetic parameters (non-displaceable binding potential, BPND). On static [18F]FDG, the mean bias for MaxProb ranged between 0 and 1% for 73 out of 84 regions assessed, and exceptionally peaked at 2.5% for only one region. Statistical parametric map analysis of MaxProb-corrected PET data showed significant differences in less than 0.02% of the brain volume, whereas SingleAtlas-corrected data showed significant differences in 20% of the brain volume. On dynamic [18F]MPPF, most regional errors on BPND ranged from -1 to  +3% (maximum bias 5%) for the MaxProb method. With SingleAtlas, errors were larger and had higher variability in most regions. PET quantification bias increased over the duration of the dynamic scan for SingleAtlas, but not for MaxProb. We show that this effect is due to the interaction of the spatial tracer-distribution heterogeneity variation over time with the degree of accuracy of the attenuation maps. This

Multi-atlas attenuation correction supports full quantification of static and dynamic brain PET data in PET-MR.

PubMed

Mérida, Inés; Reilhac, Anthonin; Redouté, Jérôme; Heckemann, Rolf A; Costes, Nicolas; Hammers, Alexander

2017-04-07

In simultaneous PET-MR, attenuation maps are not directly available. Essential for absolute radioactivity quantification, they need to be derived from MR or PET data to correct for gamma photon attenuation by the imaged object. We evaluate a multi-atlas attenuation correction method for brain imaging (MaxProb) on static [ 18 F]FDG PET and, for the first time, on dynamic PET, using the serotoninergic tracer [ 18 F]MPPF. A database of 40 MR/CT image pairs (atlases) was used. The MaxProb method synthesises subject-specific pseudo-CTs by registering each atlas to the target subject space. Atlas CT intensities are then fused via label propagation and majority voting. Here, we compared these pseudo-CTs with the real CTs in a leave-one-out design, contrasting the MaxProb approach with a simplified single-atlas method (SingleAtlas). We evaluated the impact of pseudo-CT accuracy on reconstructed PET images, compared to PET data reconstructed with real CT, at the regional and voxel levels for the following: radioactivity images; time-activity curves; and kinetic parameters (non-displaceable binding potential, BP ND ). On static [ 18 F]FDG, the mean bias for MaxProb ranged between 0 and 1% for 73 out of 84 regions assessed, and exceptionally peaked at 2.5% for only one region. Statistical parametric map analysis of MaxProb-corrected PET data showed significant differences in less than 0.02% of the brain volume, whereas SingleAtlas-corrected data showed significant differences in 20% of the brain volume. On dynamic [ 18 F]MPPF, most regional errors on BP ND ranged from -1 to  +3% (maximum bias 5%) for the MaxProb method. With SingleAtlas, errors were larger and had higher variability in most regions. PET quantification bias increased over the duration of the dynamic scan for SingleAtlas, but not for MaxProb. We show that this effect is due to the interaction of the spatial tracer-distribution heterogeneity variation over time with the degree of accuracy of the attenuation

Research on segmentation based on multi-atlas in brain MR image

NASA Astrophysics Data System (ADS)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

A Bayesian approach to the creation of a study-customized neonatal brain atlas

PubMed Central

Zhang, Yajing; Chang, Linda; Ceritoglu, Can; Skranes, Jon; Ernst, Thomas; Mori, Susumu; Miller, Michael I.; Oishi, Kenichi

2014-01-01

Atlas-based image analysis (ABA), in which an anatomical “parcellation map” is used for parcel-by-parcel image quantification, is widely used to analyze anatomical and functional changes related to brain development, aging, and various diseases. The parcellation maps are often created based on common MRI templates, which allow users to transform the template to target images, or vice versa, to perform parcel-by-parcel statistics, and report the scientific findings based on common anatomical parcels. The use of a study-specific template, which represents the anatomical features of the study population better than common templates, is preferable for accurate anatomical labeling; however, the creation of a parcellation map for a study-specific template is extremely labor intensive, and the definitions of anatomical boundaries are not necessarily compatible with those of the common template. In this study, we employed a Volume-based Template Estimation (VTE) method to create a neonatal brain template customized to a study population, while keeping the anatomical parcellation identical to that of a common MRI atlas. The VTE was used to morph the standardized parcellation map of the JHU-neonate-SS atlas to capture the anatomical features of a study population. The resultant “study-customized” T1-weighted and diffusion tensor imaging (DTI) template, with three-dimensional anatomical parcellation that defined 122 brain regions, was compared with the JHU-neonate-SS atlas, in terms of the registration accuracy. A pronounced increase in the accuracy of cortical parcellation and superior tensor alignment were observed when the customized template was used. With the customized atlas-based analysis, the fractional anisotropy (FA) detected closely approximated the manual measurements. This tool provides a solution for achieving normalization-based measurements with increased accuracy, while reporting scientific findings in a consistent framework. PMID:25026155

ABAEnrichment: an R package to test for gene set expression enrichment in the adult and developing human brain.

PubMed

Grote, Steffi; Prüfer, Kay; Kelso, Janet; Dannemann, Michael

2016-10-15

We present ABAEnrichment, an R package that tests for expression enrichment in specific brain regions at different developmental stages using expression information gathered from multiple regions of the adult and developing human brain, together with ontologically organized structural information about the brain, both provided by the Allen Brain Atlas. We validate ABAEnrichment by successfully recovering the origin of gene sets identified in specific brain cell-types and developmental stages. ABAEnrichment was implemented as an R package and is available under GPL (≥ 2) from the Bioconductor website (http://bioconductor.org/packages/3.3/bioc/html/ABAEnrichment.html). steffi_grote@eva.mpg.de, kelso@eva.mpg.de or michael_dannemann@eva.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Evaluation of Atlas-Based Attenuation Correction for Integrated PET/MR in Human Brain: Application of a Head Atlas and Comparison to True CT-Based Attenuation Correction.

PubMed

Sekine, Tetsuro; Buck, Alfred; Delso, Gaspar; Ter Voert, Edwin E G W; Huellner, Martin; Veit-Haibach, Patrick; Warnock, Geoffrey

2016-02-01

Attenuation correction (AC) for integrated PET/MR imaging in the human brain is still an open problem. In this study, we evaluated a simplified atlas-based AC (Atlas-AC) by comparing (18)F-FDG PET data corrected using either Atlas-AC or true CT data (CT-AC). We enrolled 8 patients (median age, 63 y). All patients underwent clinically indicated whole-body (18)F-FDG PET/CT for staging, restaging, or follow-up of malignant disease. All patients volunteered for an additional PET/MR of the head (additional tracer was not injected). For each patient, 2 AC maps were generated: an Atlas-AC map registered to a patient-specific liver accelerated volume acquisition-Flex MR sequence and using a vendor-provided head atlas generated from multiple CT head images and a CT-based AC map. For comparative AC, the CT-AC map generated from PET/CT was superimposed on the Atlas-AC map. PET images were reconstructed from the list-mode raw data from the PET/MR imaging scanner using each AC map. All PET images were normalized to the SPM5 PET template, and (18)F-FDG accumulation was quantified in 67 volumes of interest (VOIs; automated anatomic labeling atlas). Relative difference (%diff) between images based on Atlas-AC and CT-AC was calculated, and averaged difference images were generated. (18)F-FDG uptake in all VOIs was compared using Bland-Altman analysis. The range of error in all 536 VOIs was -3.0%-7.3%. Whole-brain (18)F-FDG uptake based on Atlas-AC was slightly underestimated (%diff = 2.19% ± 1.40%). The underestimation was most pronounced in the regions below the anterior/posterior commissure line, such as the cerebellum, temporal lobe, and central structures (%diff = 3.69% ± 1.43%, 3.25% ± 1.42%, and 3.05% ± 1.18%), suggesting that Atlas-AC tends to underestimate the attenuation values of the skull base bone. When compared with the gold-standard CT-AC, errors introduced using Atlas-AC did not exceed 8% in any brain region investigated. Underestimation of (18)F-FDG uptake was

Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool.

PubMed

Liang, Zifei; He, Xiaohai; Ceritoglu, Can; Tang, Xiaoying; Li, Yue; Kutten, Kwame S; Oishi, Kenichi; Miller, Michael I; Mori, Susumu; Faria, Andreia V

2015-01-01

Brain parcellation tools based on multiple-atlas algorithms have recently emerged as a promising method with which to accurately define brain structures. When dealing with data from various sources, it is crucial that these tools are robust for many different imaging protocols. In this study, we tested the robustness of a multiple-atlas, likelihood fusion algorithm using Alzheimer's Disease Neuroimaging Initiative (ADNI) data with six different protocols, comprising three manufacturers and two magnetic field strengths. The entire brain was parceled into five different levels of granularity. In each level, which defines a set of brain structures, ranging from eight to 286 regions, we evaluated the variability of brain volumes related to the protocol, age, and diagnosis (healthy or Alzheimer's disease). Our results indicated that, with proper pre-processing steps, the impact of different protocols is minor compared to biological effects, such as age and pathology. A precise knowledge of the sources of data variation enables sufficient statistical power and ensures the reliability of an anatomical analysis when using this automated brain parcellation tool on datasets from various imaging protocols, such as clinical databases.

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

PubMed Central

Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

2016-01-01

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI_LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Guangkai; Gao, Yaozong; Wu, Guorong

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features canmore » be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors

The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas.

PubMed

Ecker, Joseph R; Geschwind, Daniel H; Kriegstein, Arnold R; Ngai, John; Osten, Pavel; Polioudakis, Damon; Regev, Aviv; Sestan, Nenad; Wickersham, Ian R; Zeng, Hongkui

2017-11-01

A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans. Copyright © 2017 Elsevier Inc. All rights reserved.

The VALiDATe29 MRI Based Multi-Channel Atlas of the Squirrel Monkey Brain.

PubMed

Schilling, Kurt G; Gao, Yurui; Stepniewska, Iwona; Wu, Tung-Lin; Wang, Feng; Landman, Bennett A; Gore, John C; Chen, Li Min; Anderson, Adam W

2017-10-01

We describe the development of the first digital atlas of the normal squirrel monkey brain and present the resulting product, VALiDATe29. The VALiDATe29 atlas is based on multiple types of magnetic resonance imaging (MRI) contrast acquired on 29 squirrel monkeys, and is created using unbiased, nonlinear registration techniques, resulting in a population-averaged stereotaxic coordinate system. The atlas consists of multiple anatomical templates (proton density, T1, and T2* weighted), diffusion MRI templates (fractional anisotropy and mean diffusivity), and ex vivo templates (fractional anisotropy and a structural MRI). In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels. The combination of intensity templates and image segmentations make this atlas suitable for the fundamental atlas applications of spatial normalization and label propagation. Together, this atlas facilitates 3D anatomical localization and region of interest delineation, and enables comparisons of experimental data across different subjects or across different experimental conditions. This article describes the atlas creation and its contents, and demonstrates the use of the VALiDATe29 atlas in typical applications. The atlas is freely available to the scientific community.

A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability.

PubMed

Calabrese, Evan; Badea, Alexandra; Watson, Charles; Johnson, G Allan

2013-05-01

There has been growing interest in the role of postnatal brain development in the etiology of several neurologic diseases. The rat has long been recognized as a powerful model system for studying neuropathology and the safety of pharmacologic treatments. However, the complex spatiotemporal changes that occur during rat neurodevelopment remain to be elucidated. This work establishes the first magnetic resonance histology (MRH) atlas of the developing rat brain, with an emphasis on quantitation. The atlas comprises five specimens at each of nine time points, imaged with eight distinct MR contrasts and segmented into 26 developmentally defined brain regions. The atlas was used to establish a timeline of morphometric changes and variability throughout neurodevelopment and represents a quantitative database of rat neurodevelopment for characterizing rat models of human neurologic disease. Published by Elsevier Inc.

Allenes in Asymmetric Catalysis. Asymmetric Ring-Opening of Meso-Epoxides Catalyzed by Allene-Containing Phosphine Oxides

PubMed Central

Pu, Xiaotao; Qi, Xiangbing; Ready, Joseph M.

2009-01-01

Unsymmetrically substituted allenes (1,2 dienes) are inherently chiral and can be prepared in optically pure form. Nonetheless, to date the allene framework has not been incorporated into ligands for asymmetric catalysis. Since allenes project functionality differently than either tetrahedral carbon or chiral biaryls, they may create complementary chiral environments. This study demonstrates that optically active C2 symmetric allene-containing bisphosphine oxides can catalyze the addition of SiCl4 to meso epoxides with high enantioselectivity. The epoxide-opening likely involves generation of a Lewis acidic, cationic (bisphosphine oxide)SiCl3 complex. The fact that high asymmetric induction is observed suggests that allenes may represent a new platform for the development of ligands and catalysts for asymmetric synthesis. PMID:19722613

High-resolution digital brain atlases: a Hubble telescope for the brain.

PubMed

Jones, Edward G; Stone, James M; Karten, Harvey J

2011-05-01

We describe implementation of a method for digitizing at microscopic resolution brain tissue sections containing normal and experimental data and for making the content readily accessible online. Web-accessible brain atlases and virtual microscopes for online examination can be developed using existing computer and internet technologies. Resulting databases, made up of hierarchically organized, multiresolution images, enable rapid, seamless navigation through the vast image datasets generated by high-resolution scanning. Tools for visualization and annotation of virtual microscope slides enable remote and universal data sharing. Interactive visualization of a complete series of brain sections digitized at subneuronal levels of resolution offers fine grain and large-scale localization and quantification of many aspects of neural organization and structure. The method is straightforward and replicable; it can increase accessibility and facilitate sharing of neuroanatomical data. It provides an opportunity for capturing and preserving irreplaceable, archival neurohistological collections and making them available to all scientists in perpetuity, if resources could be obtained from hitherto uninterested agencies of scientific support. © 2011 New York Academy of Sciences.

A spatiotemporal atlas of MR intensity, tissue probability and shape of the fetal brain with application to segmentation

PubMed Central

Habas, Piotr A.; Kim, Kio; Corbett-Detig, James M.; Rousseau, Francois; Glenn, Orit A.; Barkovich, A. James; Studholme, Colin

2010-01-01

Modeling and analysis of MR images of the developing human brain is a challenge due to rapid changes in brain morphology and morphometry. We present an approach to the construction of a spatiotemporal atlas of the fetal brain with temporal models of MR intensity, tissue probability and shape changes. This spatiotemporal model is created from a set of reconstructed MR images of fetal subjects with different gestational ages. Groupwise registration of manual segmentations and voxelwise nonlinear modeling allow us to capture the appearance, disappearance and spatial variation of brain structures over time. Applying this model to atlas-based segmentation, we generate age-specific MR templates and tissue probability maps and use them to initialize automatic tissue delineation in new MR images. The choice of model parameters and the final performance are evaluated using clinical MR scans of young fetuses with gestational ages ranging from 20.57 to 24.71 weeks. Experimental results indicate that quadratic temporal models can correctly capture growth-related changes in the fetal brain anatomy and provide improvement in accuracy of atlas-based tissue segmentation. PMID:20600970

Accurate Learning with Few Atlases (ALFA): an algorithm for MRI neonatal brain extraction and comparison with 11 publicly available methods.

PubMed

Serag, Ahmed; Blesa, Manuel; Moore, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Wilkinson, A G; Macnaught, Gillian; Semple, Scott I; Boardman, James P

2016-03-24

Accurate whole-brain segmentation, or brain extraction, of magnetic resonance imaging (MRI) is a critical first step in most neuroimage analysis pipelines. The majority of brain extraction algorithms have been developed and evaluated for adult data and their validity for neonatal brain extraction, which presents age-specific challenges for this task, has not been established. We developed a novel method for brain extraction of multi-modal neonatal brain MR images, named ALFA (Accurate Learning with Few Atlases). The method uses a new sparsity-based atlas selection strategy that requires a very limited number of atlases 'uniformly' distributed in the low-dimensional data space, combined with a machine learning based label fusion technique. The performance of the method for brain extraction from multi-modal data of 50 newborns is evaluated and compared with results obtained using eleven publicly available brain extraction methods. ALFA outperformed the eleven compared methods providing robust and accurate brain extraction results across different modalities. As ALFA can learn from partially labelled datasets, it can be used to segment large-scale datasets efficiently. ALFA could also be applied to other imaging modalities and other stages across the life course.

A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

PubMed Central

Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

Common Genetic Variant in VIT Is Associated with Human Brain Asymmetry.

PubMed

Tadayon, Sayed H; Vaziri-Pashkam, Maryam; Kahali, Pegah; Ansari Dezfouli, Mitra; Abbassian, Abdolhossein

2016-01-01

Brain asymmetry varies across individuals. However, genetic factors contributing to this normal variation are largely unknown. Here we studied variation of cortical surface area asymmetry in a large sample of subjects. We performed principal component analysis (PCA) to capture correlated asymmetry variation across cortical regions. We found that caudal and rostral anterior cingulate together account for a substantial part of asymmetry variation among individuals. To find SNPs associated with this subset of brain asymmetry variation we performed a genome-wide association study followed by replication in an independent cohort. We identified one SNP (rs11691187) that had genome-wide significant association (P Combined = 2.40e-08). The rs11691187 is in the first intron of VIT. In a follow-up analysis, we found that VIT gene expression is associated with brain asymmetry in six donors of the Allen Human Brain Atlas. Based on these findings we suggest that VIT contributes to normal brain asymmetry variation. Our results can shed light on disorders associated with altered brain asymmetry.

The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization

PubMed Central

Rohlfing, Torsten; Kroenke, Christopher D.; Sullivan, Edith V.; Dubach, Mark F.; Bowden, Douglas M.; Grant, Kathleen A.; Pfefferbaum, Adolf

2012-01-01

The INIA19 is a new, high-quality template for imaging-based studies of non-human primate brains, created from high-resolution, T1-weighted magnetic resonance (MR) images of 19 rhesus macaque (Macaca mulatta) animals. Combined with the comprehensive cortical and sub-cortical label map of the NeuroMaps atlas, the INIA19 is equally suitable for studies requiring both spatial normalization and atlas label propagation. Population-averaged template images are provided for both the brain and the whole head, to allow alignment of the atlas with both skull-stripped and unstripped data, and thus to facilitate its use for skull stripping of new images. This article describes the construction of the template using freely available software tools, as well as the template itself, which is being made available to the scientific community (http://nitrc.org/projects/inia19/). PMID:23230398

The Brain of the Archerfish Toxotes chatareus: A Nissl-Based Neuroanatomical Atlas and Catecholaminergic/Cholinergic Systems

PubMed Central

Karoubi, Naomi; Segev, Ronen; Wullimann, Mario F.

2016-01-01

Over recent years, the seven-spot archerfish (Toxotes chatareus) has emerged as a new model for studies in visual and behavioral neuroscience thanks to its unique hunting strategy. Its natural ability to spit at insects outside of water can be used in the laboratory for well controlled behavioral experiments where the fish is trained to aim at targets on a screen. The need for a documentation of the neuroanatomy of this animal became critical as more research groups use it as a model. Here we present an atlas of adult T. chatareus specimens caught in the wild in South East Asia. The atlas shows representative sections of the brain and specific structures revealed by a classic Nissl staining as well as corresponding schematic drawings. Additional immunostainings for catecholaminergic and cholinergic systems were conducted to corroborate the identification of certain nuclei and the data of a whole brain scanner is available online. We describe the general features of the archerfish brain as well as its specificities, especially for the visual system and compare the neuroanatomy of the archerfish with other teleosts. This atlas of the archerfish brain shows all levels of the neuraxis and intends to provide a solid basis for further neuroscientific research on T. chatareus, in particular electrophysiological studies. PMID:27891081

Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity.

PubMed

Ewert, Siobhan; Plettig, Philip; Li, Ningfei; Chakravarty, M Mallar; Collins, D Louis; Herrington, Todd M; Kühn, Andrea A; Horn, Andreas

2018-04-15

Three-dimensional atlases of subcortical brain structures are valuable tools to reference anatomy in neuroscience and neurology. For instance, they can be used to study the position and shape of the three most common deep brain stimulation (DBS) targets, the subthalamic nucleus (STN), internal part of the pallidum (GPi) and ventral intermediate nucleus of the thalamus (VIM) in spatial relationship to DBS electrodes. Here, we present a composite atlas based on manual segmentations of a multimodal high resolution brain template, histology and structural connectivity. In a first step, four key structures were defined on the template itself using a combination of multispectral image analysis and manual segmentation. Second, these structures were used as anchor points to coregister a detailed histological atlas into standard space. Results show that this approach significantly improved coregistration accuracy over previously published methods. Finally, a sub-segmentation of STN and GPi into functional zones was achieved based on structural connectivity. The result is a composite atlas that defines key nuclei on the template itself, fills the gaps between them using histology and further subdivides them using structural connectivity. We show that the atlas can be used to segment DBS targets in single subjects, yielding more accurate results compared to priorly published atlases. The atlas will be made publicly available and constitutes a resource to study DBS electrode localizations in combination with modern neuroimaging methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Stereotaxic 18F-FDG PET and MRI templates with three-dimensional digital atlas for statistical parametric mapping analysis of tree shrew brain.

PubMed

Huang, Qi; Nie, Binbin; Ma, Chen; Wang, Jing; Zhang, Tianhao; Duan, Shaofeng; Wu, Shang; Liang, Shengxiang; Li, Panlong; Liu, Hua; Sun, Hua; Zhou, Jiangning; Xu, Lin; Shan, Baoci

2018-01-01

Tree shrews are proposed as an alternative animal model to nonhuman primates due to their close affinity to primates. Neuroimaging techniques are widely used to study brain functions and structures of humans and animals. However, tree shrews are rarely applied in neuroimaging field partly due to the lack of available species specific analysis methods. In this study, 10 PET/CT and 10 MRI images of tree shrew brain were used to construct PET and MRI templates; based on histological atlas we reconstructed a three-dimensional digital atlas with 628 structures delineated; then the digital atlas and templates were aligned into a stereotaxic space. Finally, we integrated the digital atlas and templates into a toolbox for tree shrew brain spatial normalization, statistical analysis and results localization. We validated the feasibility of the toolbox by simulated data with lesions in laterodorsal thalamic nucleus (LD). The lesion volumes of simulated PET and MRI images were (12.97±3.91)mm 3 and (7.04±0.84)mm 3 . Statistical results at p<0.005 showed the lesion volumes of PET and MRI were 13.18mm 3 and 8.06mm 3 in LD. To our knowledge, we report the first PET template and digital atlas of tree shrew brain. Compared to the existing MRI templates, our MRI template was aligned into stereotaxic space. And the toolbox is the first software dedicated for tree shrew brain analysis. The templates and digital atlas of tree shrew brain, as well as the toolbox, facilitate the use of tree shrews in neuroimaging field. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence of signal intensity non-uniformity on brain volumetry using an atlas-based method.

PubMed

Goto, Masami; Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.

Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method

PubMed Central

Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Objective Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials. PMID:22778560

Computation of an MRI brain atlas from a population of Parkinson’s disease patients

NASA Astrophysics Data System (ADS)

Angelidakis, L.; Papageorgiou, I. E.; Damianou, C.; Psychogios, M. N.; Lingor, P.; von Eckardstein, K.; Hadjidemetriou, S.

2017-11-01

Parkinson’s Disease (PD) is a degenerative disorder of the brain. This study presents an MRI-based brain atlas of PD to characterize associated alterations for diagnostic and interventional purposes. The atlas standardizes primarily the implicated subcortical regions such as the globus pallidus (GP), substantia nigra (SN), subthalamic nucleus (STN), caudate nucleus (CN), thalamus (TH), putamen (PUT), and red nucleus (RN). The data were 3.0 T MRI brain images from 16 PD patients and 10 matched controls. The images used were T1-weighted (T 1 w), T2-weighted (T 2 w) images, and Susceptibility Weighted Images (SWI). The T1w images were the reference for the inter-subject non-rigid registration available from 3DSlicer. Anatomic labeling was achieved with BrainSuite and regions were refined with the level sets segmentation of ITK-Snap. The subcortical centers were analyzed for their volume and signal intensity. Comparison with an age-matched control group unravels a significant PD-related T1w signal loss in the striatum (CN and PUT) centers, but approximately a constant volume. The results in this study improve MRI based PD localization and can lead to the development of novel biomarkers.

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas

PubMed Central

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G.; Leergaard, Trygve B.; Kirlangic, Mehmet E.; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space

3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas.

PubMed

Schubert, Nicole; Axer, Markus; Schober, Martin; Huynh, Anh-Minh; Huysegoms, Marcel; Palomero-Gallagher, Nicola; Bjaalie, Jan G; Leergaard, Trygve B; Kirlangic, Mehmet E; Amunts, Katrin; Zilles, Karl

2016-01-01

High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

A three-dimensional stereotaxic MRI brain atlas of the cichlid fish Oreochromis mossambicus.

PubMed

Simões, José M; Teles, Magda C; Oliveira, Rui F; Van der Linden, Annemie; Verhoye, Marleen

2012-01-01

The African cichlid Oreochromis mossambicus (Mozambique tilapia) has been used as a model system in a wide range of behavioural and neurobiological studies. The increasing number of genetic tools available for this species, together with the emerging interest in its use for neurobiological studies, increased the need for an accurate hodological mapping of the tilapia brain to supplement the available histological data. The goal of our study was to elaborate a three-dimensional, high-resolution digital atlas using magnetic resonance imaging, supported by Nissl staining. Resulting images were viewed and analysed in all orientations (transverse, sagittal, and horizontal) and manually labelled to reveal structures in the olfactory bulb, telencephalon, diencephalon, optic tectum, and cerebellum. This high resolution tilapia brain atlas is expected to become a very useful tool for neuroscientists using this fish model and will certainly expand their use in future studies regarding the central nervous system.

Genomic connectivity networks based on the BrainSpan atlas of the developing human brain

NASA Astrophysics Data System (ADS)

Mahfouz, Ahmed; Ziats, Mark N.; Rennert, Owen M.; Lelieveldt, Boudewijn P. F.; Reinders, Marcel J. T.

2014-03-01

The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

A histology-based atlas of the C57BL/6J mouse brain deformably registered to in vivo MRI for localized radiation and surgical targeting

NASA Astrophysics Data System (ADS)

Purger, David; McNutt, Todd; Achanta, Pragathi; Quiñones-Hinojosa, Alfredo; Wong, John; Ford, Eric

2009-12-01

The C57BL/6J laboratory mouse is commonly used in neurobiological research. Digital atlases of the C57BL/6J brain have been used for visualization, genetic phenotyping and morphometry, but currently lack the ability to accurately calculate deviations between individual mice. We developed a fully three-dimensional digital atlas of the C57BL/6J brain based on the histology atlas of Paxinos and Franklin (2001 The Mouse Brain in Stereotaxic Coordinates 2nd edn (San Diego, CA: Academic)). The atlas uses triangular meshes to represent the various structures. The atlas structures can be overlaid and deformed to individual mouse MR images. For this study, we selected 18 structures from the histological atlas. Average atlases can be created for any group of mice of interest by calculating the mean three-dimensional positions of corresponding individual mesh vertices. As a validation of the atlas' accuracy, we performed deformable registration of the lateral ventricles to 13 MR brain scans of mice in three age groups: 5, 8 and 9 weeks old. Lateral ventricle structures from individual mice were compared to the corresponding average structures and the original histology structures. We found that the average structures created using our method more accurately represent individual anatomy than histology-based atlases alone, with mean vertex deviations of 0.044 mm versus 0.082 mm for the left lateral ventricle and 0.045 mm versus 0.068 mm for the right lateral ventricle. Our atlas representation gives direct spatial deviations for structures of interest. Our results indicate that MR-deformable histology-based atlases represent an accurate method to obtain accurate morphometric measurements of a population of mice, and that this method may be applied to phenotyping experiments in the future as well as precision targeting of surgical procedures or radiation treatment.

Specifying the brain anatomy underlying temporo-parietal junction activations for theory of mind: A review using probabilistic atlases from different imaging modalities.

PubMed

Schurz, Matthias; Tholen, Matthias G; Perner, Josef; Mars, Rogier B; Sallet, Jerome

2017-09-01

In this quantitative review, we specified the anatomical basis of brain activity reported in the Temporo-Parietal Junction (TPJ) in Theory of Mind (ToM) research. Using probabilistic brain atlases, we labeled TPJ peak coordinates reported in the literature. This was carried out for four different atlas modalities: (i) gyral-parcellation, (ii) sulco-gyral parcellation, (iii) cytoarchitectonic parcellation and (iv) connectivity-based parcellation. In addition, our review distinguished between two ToM task types (false belief and social animations) and a nonsocial task (attention reorienting). We estimated the mean probabilities of activation for each atlas label, and found that for all three task types part of TPJ activations fell into the same areas: (i) Angular Gyrus (AG) and Lateral Occpital Cortex (LOC) in terms of a gyral atlas, (ii) AG and Superior Temporal Sulcus (STS) in terms of a sulco-gyral atlas, (iii) areas PGa and PGp in terms of cytoarchitecture and (iv) area TPJp in terms of a connectivity-based parcellation atlas. Beside these commonalities, we also found that individual task types showed preferential activation for particular labels. Main findings for the right hemisphere were preferential activation for false belief tasks in AG/PGa, and in Supramarginal Gyrus (SMG)/PFm for attention reorienting. Social animations showed strongest selective activation in the left hemisphere, specifically in left Middle Temporal Gyrus (MTG). We discuss how our results (i.e., identified atlas structures) can provide a new reference for describing future findings, with the aim to integrate different labels and terminologies used for studying brain activity around the TPJ. Hum Brain Mapp 38:4788-4805, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Brain maps 4.0—Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps

PubMed Central

2018-01-01

Abstract The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature tables that define and describe all parts of the rat nervous system within the framework of a strictly topographic system devised previously for the human nervous system. These tables constitute a global ontology for knowledge management systems dealing with neural circuitry. A second new feature is an aligned atlas of bilateral flatmaps illustrating rat nervous system development from the neural plate stage to the adult stage, where most gray matter regions, white matter tracts, ganglia, and nerves listed in the nomenclature tables are illustrated schematically. These flatmaps are convenient for future development of online applications analogous to “Google Maps” for systems neuroscience. The third new feature is a completely revised Atlas of the rat brain in spatially aligned transverse sections that can serve as a framework for 3‐D modeling. Atlas parcellation is little changed from the preceding edition, but the nomenclature for rat is now aligned with an emerging panmammalian neuroanatomical nomenclature. All figures are presented in Adobe Illustrator vector graphics format that can be manipulated, modified, and resized as desired, and freely used with a Creative Commons license. PMID:29277900

Brain maps 4.0-Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps.

PubMed

Swanson, Larry W

2018-04-15

The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature tables that define and describe all parts of the rat nervous system within the framework of a strictly topographic system devised previously for the human nervous system. These tables constitute a global ontology for knowledge management systems dealing with neural circuitry. A second new feature is an aligned atlas of bilateral flatmaps illustrating rat nervous system development from the neural plate stage to the adult stage, where most gray matter regions, white matter tracts, ganglia, and nerves listed in the nomenclature tables are illustrated schematically. These flatmaps are convenient for future development of online applications analogous to "Google Maps" for systems neuroscience. The third new feature is a completely revised Atlas of the rat brain in spatially aligned transverse sections that can serve as a framework for 3-D modeling. Atlas parcellation is little changed from the preceding edition, but the nomenclature for rat is now aligned with an emerging panmammalian neuroanatomical nomenclature. All figures are presented in Adobe Illustrator vector graphics format that can be manipulated, modified, and resized as desired, and freely used with a Creative Commons license. © 2018 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Stereoselective rhodium-catalysed [2+2+2] cycloaddition of linear allene-ene/yne-allene substrates: reactivity and theoretical mechanistic studies.

PubMed

Haraburda, Ewelina; Torres, Óscar; Parella, Teodor; Solà, Miquel; Pla-Quintana, Anna

2014-04-22

Allene-ene-allene (2 and 5) and allene-yne-allene (3 and 7) N-tosyl and O-linked substrates were satisfactorily synthesised. The [2+2+2] cycloaddition reaction catalysed by the Wilkinson catalyst [RhCl(PPh3 )3 ] was evaluated. Substrates 2 and 5, which bear a double bond in the central position, gave a tricyclic structure in a reaction in which four contiguous stereogenic centres were formed as a single diastereomer. The reaction of substrates 3 and 7, which bear a triple bond in the central position, gave a tricyclic structure with a cyclohexenic ring core, again in a diastereoselective manner. All cycloadducts were formed by a regioselective reaction of the inner allene double bond and, therefore, feature an exocyclic diene motif. A Diels-Alder reaction on N-tosyl linked cycloadducts 8 and 10 allowed pentacyclic scaffolds to be diastereoselectively constructed. The reactivity of the allenes on [2+2+2] cycloaddition reactions was studied for the first time by density functional theory calculations. This mechanistic study rationalizes the order in which the unsaturations take part in the catalytic cycle, the reactivity of the two double bonds of the allene towards the [2+2+2] cycloaddition reaction, and the diastereoselectivity of the reaction. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data

PubMed Central

Calabrese, Evan; Badea, Alexandra; Cofer, Gary; Qi, Yi; Johnson, G. Allan

2015-01-01

Interest in structural brain connectivity has grown with the understanding that abnormal neural connections may play a role in neurologic and psychiatric diseases. Small animal connectivity mapping techniques are particularly important for identifying aberrant connectivity in disease models. Diffusion magnetic resonance imaging tractography can provide nondestructive, 3D, brain-wide connectivity maps, but has historically been limited by low spatial resolution, low signal-to-noise ratio, and the difficulty in estimating multiple fiber orientations within a single image voxel. Small animal diffusion tractography can be substantially improved through the combination of ex vivo MRI with exogenous contrast agents, advanced diffusion acquisition and reconstruction techniques, and probabilistic fiber tracking. Here, we present a comprehensive, probabilistic tractography connectome of the mouse brain at microscopic resolution, and a comparison of these data with a neuronal tracer-based connectivity data from the Allen Brain Atlas. This work serves as a reference database for future tractography studies in the mouse brain, and demonstrates the fundamental differences between tractography and neuronal tracer data. PMID:26048951

Brain in situ hybridization maps as a source for reverse-engineering transcriptional regulatory networks: Alzheimer's disease insights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Acquaah-Mensah, George K.; Taylor, Ronald C.

Microarray data have been a valuable resource for identifying transcriptional regulatory relationships among genes. As an example, brain region-specific transcriptional regulatory events have the potential of providing etiological insights into Alzheimer Disease (AD). However, there is often a paucity of suitable brain-region specific expression data obtained via microarrays or other high throughput means. The Allen Brain Atlas in situ hybridization (ISH) data sets (Jones et al., 2009) represent a potentially valuable alternative source of high-throughput brain region-specific gene expression data for such purposes. In this study, Allen BrainAtlasmouse ISH data in the hippocampal fields were extracted, focusing on 508 genesmore » relevant to neurodegeneration. Transcriptional regulatory networkswere learned using three high-performing network inference algorithms. Only 17% of regulatory edges from a network reverse-engineered based on brain region-specific ISH data were also found in a network constructed upon gene expression correlations inmousewhole brain microarrays, thus showing the specificity of gene expression within brain sub-regions. Furthermore, the ISH data-based networks were used to identify instructive transcriptional regulatory relationships. Ncor2, Sp3 and Usf2 form a unique three-party regulatory motif, potentially affecting memory formation pathways. Nfe2l1, Egr1 and Usf2 emerge among regulators of genes involved in AD (e.g. Dhcr24, Aplp2, Tia1, Pdrx1, Vdac1, andSyn2). Further, Nfe2l1, Egr1 and Usf2 are sensitive to dietary factors and could be among links between dietary influences and genes in the AD etiology. Thus, this approach of harnessing brain region-specific ISH data represents a rare opportunity for gleaning unique etiological insights for diseases such as AD.« less

Obituary: James Alfred Van Allen, 1914-2006

NASA Astrophysics Data System (ADS)

Ludwig, George H.; McIlwain, Carl Edwin

2006-12-01

James Alfred Van Allen, world-renowned space scientist, died 9 August 2006 at the age of ninety-one. He succumbed to heart failure after a ten-week period of declining health. Van Allen served for his entire sixty-seven-year professional career as an amazingly productive researcher, space science spokesman, inspired teacher, and valued colleague. The realization by him and his associates that charged particles are trapped by the Earth's magnetic field began a whole new field of research, magnetospheric physics. Following that initial discovery, he and his associates quickly extended their observations, first to the inner planets, and then to the rest of the planets and beyond. During his tenure at Iowa, he and his group flew instruments on more than sixty successful Earth satellites and planetary spacecraft, including the first missions to the planets Venus, Mars, Jupiter, Saturn, Uranus, and Neptune. Van Allen's lifetime publication list numbers more than 275, of which many are widely-cited, seminal papers. He was the sole author of more than 125 of those papers. Beyond the research laboratory, Van Allen worked energetically throughout his career in establishing space research as a new branch of human inquiry. He was among the most sought-after as a committee member and adviser, working at the highest levels of government, including the White House and Congress, and at all levels of the national and international research establishments. Many presentations in the non-scientific arena helped to bring the exciting discoveries and challenges of space research to the attention of the general public. James Van Allen (Van to his many friends and colleagues) was born on 7 September 1914 on a small farm near Mount Pleasant, Iowa, the second of four sons of Alfred Morris Van Allen and Alma Olney Van Allen. After high school in Mount Pleasant, he entered Iowa Wesleyan College, majoring in physics and graduating summa cum laude. While there, he was introduced to geophysics

33 CFR 165.T08-0432 - Safety Zone; Waterway Closure, Morgan City-Port Allen Route from Mile Marker 0 to Port Allen Lock.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., Morgan City-Port Allen Route from Mile Marker 0 to Port Allen Lock. 165.T08-0432 Section 165.T08-0432... Limited Access Areas Eighth Coast Guard District § 165.T08-0432 Safety Zone; Waterway Closure, Morgan City... Water Way on the Morgan City—Port Allen route from MM 0 to the Port Allen lock. (b) Effective date. This...

Regional growth and atlasing of the developing human brain

PubMed Central

Makropoulos, Antonios; Aljabar, Paul; Wright, Robert; Hüning, Britta; Merchant, Nazakat; Arichi, Tomoki; Tusor, Nora; Hajnal, Joseph V.; Edwards, A. David; Counsell, Serena J.; Rueckert, Daniel

2016-01-01

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45 weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area. PMID:26499811

Regional growth and atlasing of the developing human brain.

PubMed

Makropoulos, Antonios; Aljabar, Paul; Wright, Robert; Hüning, Britta; Merchant, Nazakat; Arichi, Tomoki; Tusor, Nora; Hajnal, Joseph V; Edwards, A David; Counsell, Serena J; Rueckert, Daniel

2016-01-15

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area. Copyright © 2015 The Authors. Published by

Automatic Testing and Assessment of Neuroanatomy Using a Digital Brain Atlas: Method and Development of Computer- and Mobile-Based Applications

ERIC Educational Resources Information Center

Nowinski, Wieslaw L.; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G.; Marchenko, Yevgen; Volkau, Ihar

2009-01-01

Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to "Terminologia…

Automated generation of massive image knowledge collections using Microsoft Live Labs Pivot to promote neuroimaging and translational research.

PubMed

Viangteeravat, Teeradache; Anyanwu, Matthew N; Ra Nagisetty, Venkateswara; Kuscu, Emin

2011-07-15

Massive datasets comprising high-resolution images, generated in neuro-imaging studies and in clinical imaging research, are increasingly challenging our ability to analyze, share, and filter such images in clinical and basic translational research. Pivot collection exploratory analysis provides each user the ability to fully interact with the massive amounts of visual data to fully facilitate sufficient sorting, flexibility and speed to fluidly access, explore or analyze the massive image data sets of high-resolution images and their associated meta information, such as neuro-imaging databases from the Allen Brain Atlas. It is used in clustering, filtering, data sharing and classifying of the visual data into various deep zoom levels and meta information categories to detect the underlying hidden pattern within the data set that has been used. We deployed prototype Pivot collections using the Linux CentOS running on the Apache web server. We also tested the prototype Pivot collections on other operating systems like Windows (the most common variants) and UNIX, etc. It is demonstrated that the approach yields very good results when compared with other approaches used by some researchers for generation, creation, and clustering of massive image collections such as the coronal and horizontal sections of the mouse brain from the Allen Brain Atlas. Pivot visual analytics was used to analyze a prototype of dataset Dab2 co-expressed genes from the Allen Brain Atlas. The metadata along with high-resolution images were automatically extracted using the Allen Brain Atlas API. It is then used to identify the hidden information based on the various categories and conditions applied by using options generated from automated collection. A metadata category like chromosome, as well as data for individual cases like sex, age, and plan attributes of a particular gene, is used to filter, sort and to determine if there exist other genes with a similar characteristics to Dab2. And

Automated generation of massive image knowledge collections using Microsoft Live Labs Pivot to promote neuroimaging and translational research

PubMed Central

2011-01-01

Background Massive datasets comprising high-resolution images, generated in neuro-imaging studies and in clinical imaging research, are increasingly challenging our ability to analyze, share, and filter such images in clinical and basic translational research. Pivot collection exploratory analysis provides each user the ability to fully interact with the massive amounts of visual data to fully facilitate sufficient sorting, flexibility and speed to fluidly access, explore or analyze the massive image data sets of high-resolution images and their associated meta information, such as neuro-imaging databases from the Allen Brain Atlas. It is used in clustering, filtering, data sharing and classifying of the visual data into various deep zoom levels and meta information categories to detect the underlying hidden pattern within the data set that has been used. Method We deployed prototype Pivot collections using the Linux CentOS running on the Apache web server. We also tested the prototype Pivot collections on other operating systems like Windows (the most common variants) and UNIX, etc. It is demonstrated that the approach yields very good results when compared with other approaches used by some researchers for generation, creation, and clustering of massive image collections such as the coronal and horizontal sections of the mouse brain from the Allen Brain Atlas. Results Pivot visual analytics was used to analyze a prototype of dataset Dab2 co-expressed genes from the Allen Brain Atlas. The metadata along with high-resolution images were automatically extracted using the Allen Brain Atlas API. It is then used to identify the hidden information based on the various categories and conditions applied by using options generated from automated collection. A metadata category like chromosome, as well as data for individual cases like sex, age, and plan attributes of a particular gene, is used to filter, sort and to determine if there exist other genes with a similar

Chiral allene-containing phosphines in asymmetric catalysis

PubMed Central

Cai, Feng; Pu, Xiaotao; Qi, Xiangbing; Lynch, Vincent; Radha, Akella; Ready, Joseph M.

2011-01-01

Traditionally, ligands used in asymmetric catalysis have contained either stereogenic atoms or hindered single bonds (atropisomerism), or both. Here we demonstrate that allenes, chiral 1,2-dienes, appended with basic functionality can serve as ligands for transition metals. We describe an allene-containing bisphosphine that, when coordinated to Rh(I), promotes the asymmetric addition of aryl boronic acids to α-keto esters with high enantioselectivity. Solution and solid-state structural analysis reveals that one olefin of the allene can coordinate to transition metals generating bi- and tri-dentate ligands. PMID:21972824

A digital interactive human brain atlas based on Chinese visible human datasets for anatomy teaching.

PubMed

Li, Qiyu; Ran, Xu; Zhang, Shaoxiang; Tan, Liwen; Qiu, Mingguo

2014-01-01

As we know, the human brain is one of the most complicated organs in the human body, which is the key and difficult point in neuroanatomy and sectional anatomy teaching. With the rapid development and extensive application of imaging technology in clinical diagnosis, doctors are facing higher and higher requirement on their anatomy knowledge. Thus, to cultivate medical students to meet the needs of medical development today and to improve their ability to read and understand radiographic images have become urgent challenges for the medical teachers. In this context, we developed a digital interactive human brain atlas based on the Chinese visible human datasets for anatomy teaching (available for free download from http://www.chinesevisiblehuman.com/down/DHBA.rar). The atlas simultaneously provides views in all 3 primary planes of section. The main structures of the human brain have been anatomically labeled in all 3 views. It is potentially useful for anatomy browsing, user self-testing, and automatic student assessment. In a word, it is interactive, 3D, user friendly, and free of charge, which can provide a new, intuitive means for anatomy teaching.

Direct transformation of silyl enol ethers into functionalized allenes.

PubMed

Langer, P; Döring, M; Seyferth, D; Görls, H

2001-02-02

The first elimination reactions of silyl enol ethers to lithiated allenes are reported. These reactions allow a direct transformation of readily available silyl enol ethers into functionalized allenes. The action of three to four equivalents of lithium diisopropylamide (LDA) on silyl enol ethers results in the formation of lithiated allenes by initial allylic lithiation, subsequent elimination of a lithium silanolate, and finally, lithiation of the allene thus formed. Starting with amide-derived silyl imino ethers, lithiated ketenimines are obtained. A variety of reactions of the lithiated allenes with electrophiles (chlorosilanes, trimethylchlorostannane, dimethyl sulfate and ethanol) were carried out. Elimination of silanolate is observed only for substrates that contain the hindered SiMe2tBu or Si(iPr)3 moiety, but not for the SiMe3 group. The reaction of 1,1-dilithio-3,3-diphenylallene with ketones provides a convenient access to novel 1,1-di(hydroxymethyl)allenes which undergo a domino Nazarov-Friedel-Crafts reaction upon treatment with p-toluenesulfonic acid.

Multiscale Exploration of Mouse Brain Microstructures Using the Knife-Edge Scanning Microscope Brain Atlas

PubMed Central

Chung, Ji Ryang; Sung, Chul; Mayerich, David; Kwon, Jaerock; Miller, Daniel E.; Huffman, Todd; Keyser, John; Abbott, Louise C.; Choe, Yoonsuck

2011-01-01

Connectomics is the study of the full connection matrix of the brain. Recent advances in high-throughput, high-resolution 3D microscopy methods have enabled the imaging of whole small animal brains at a sub-micrometer resolution, potentially opening the road to full-blown connectomics research. One of the first such instruments to achieve whole-brain-scale imaging at sub-micrometer resolution is the Knife-Edge Scanning Microscope (KESM). KESM whole-brain data sets now include Golgi (neuronal circuits), Nissl (soma distribution), and India ink (vascular networks). KESM data can contribute greatly to connectomics research, since they fill the gap between lower resolution, large volume imaging methods (such as diffusion MRI) and higher resolution, small volume methods (e.g., serial sectioning electron microscopy). Furthermore, KESM data are by their nature multiscale, ranging from the subcellular to the whole organ scale. Due to this, visualization alone is a huge challenge, before we even start worrying about quantitative connectivity analysis. To solve this issue, we developed a web-based neuroinformatics framework for efficient visualization and analysis of the multiscale KESM data sets. In this paper, we will first provide an overview of KESM, then discuss in detail the KESM data sets and the web-based neuroinformatics framework, which is called the KESM brain atlas (KESMBA). Finally, we will discuss the relevance of the KESMBA to connectomics research, and identify challenges and future directions. PMID:22275895

Trans-cranial opening of the blood-brain barrier in targeted regions using a stereotaxic brain atlas and focused ultrasound energy.

PubMed

Bing, Chenchen; Ladouceur-Wodzak, Michelle; Wanner, Clinton R; Shelton, John M; Richardson, James A; Chopra, Rajiv

2014-01-01

The blood-brain barrier (BBB) protects the brain by preventing the entry of large molecules; this poses a major obstacle for the delivery of drugs to the brain. A novel technique using focused ultrasound (FUS) energy combined with microbubble contrast agents has been widely used for non-invasive trans-cranial BBB opening. Traditionally, FUS research is conducted with magnetic resonance imaging (MRI) guidance, which is expensive and poses physical limitations due to the magnetic field. A system that could allow researchers to test brain therapies without MR intervention could facilitate and accelerate translational research. In this study, we present a novel FUS system that uses a custom-built FUS generator mounted on a motorized stereotaxic apparatus with embedded brain atlas to locally open the BBB in rodents. The system was initially characterized using a tissue-mimicking phantom. Rodent studies were also performed to evaluate whether non-invasive, localized BBB opening could be achieved using brain atlas-based targeting. Brains were exposed to pulsed focused ultrasound energy at 1.06 MHz in rats and 3.23 MHz in mice, with the focal pressure estimated to be 0.5-0.6 MPa through the skull. BBB opening was confirmed in gross tissue sections by the presence of Evans blue leakage in the exposed region of the brain and by histological assessment. The targeting accuracy of the stereotaxic system was better than 0.5 mm in the tissue-mimicking phantom. Reproducible localized BBB opening was verified with Evans blue dye leakage in 32/33 rats and had a targeting accuracy of ±0.3 mm. The use of higher frequency exposures in mice enabled a similar precision of localized BBB opening as was observed with the low frequency in the rat model. With this dedicated small-animal motorized stereotaxic-FUS system, we achieved accurate targeting of focused ultrasound exposures in the brain for non-invasive opening of the BBB. This system can be used as an alternative to MR

An anatomically comprehensive atlas of the adult human brain transcriptome

PubMed Central

Guillozet-Bongaarts, Angela L.; Shen, Elaine H.; Ng, Lydia; Miller, Jeremy A.; van de Lagemaat, Louie N.; Smith, Kimberly A.; Ebbert, Amanda; Riley, Zackery L.; Abajian, Chris; Beckmann, Christian F.; Bernard, Amy; Bertagnolli, Darren; Boe, Andrew F.; Cartagena, Preston M.; Chakravarty, M. Mallar; Chapin, Mike; Chong, Jimmy; Dalley, Rachel A.; David Daly, Barry; Dang, Chinh; Datta, Suvro; Dee, Nick; Dolbeare, Tim A.; Faber, Vance; Feng, David; Fowler, David R.; Goldy, Jeff; Gregor, Benjamin W.; Haradon, Zeb; Haynor, David R.; Hohmann, John G.; Horvath, Steve; Howard, Robert E.; Jeromin, Andreas; Jochim, Jayson M.; Kinnunen, Marty; Lau, Christopher; Lazarz, Evan T.; Lee, Changkyu; Lemon, Tracy A.; Li, Ling; Li, Yang; Morris, John A.; Overly, Caroline C.; Parker, Patrick D.; Parry, Sheana E.; Reding, Melissa; Royall, Joshua J.; Schulkin, Jay; Sequeira, Pedro Adolfo; Slaughterbeck, Clifford R.; Smith, Simon C.; Sodt, Andy J.; Sunkin, Susan M.; Swanson, Beryl E.; Vawter, Marquis P.; Williams, Derric; Wohnoutka, Paul; Zielke, H. Ronald; Geschwind, Daniel H.; Hof, Patrick R.; Smith, Stephen M.; Koch, Christof; Grant, Seth G. N.; Jones, Allan R.

2014-01-01

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography— the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function. PMID:22996553

Neonatal Atlas Construction Using Sparse Representation

PubMed Central

Shi, Feng; Wang, Li; Wu, Guorong; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Atlas construction generally includes first an image registration step to normalize all images into a common space and then an atlas building step to fuse the information from all the aligned images. Although numerous atlas construction studies have been performed to improve the accuracy of the image registration step, unweighted or simply weighted average is often used in the atlas building step. In this article, we propose a novel patch-based sparse representation method for atlas construction after all images have been registered into the common space. By taking advantage of local sparse representation, more anatomical details can be recovered in the built atlas. To make the anatomical structures spatially smooth in the atlas, the anatomical feature constraints on group structure of representations and also the overlapping of neighboring patches are imposed to ensure the anatomical consistency between neighboring patches. The proposed method has been applied to 73 neonatal MR images with poor spatial resolution and low tissue contrast, for constructing a neonatal brain atlas with sharp anatomical details. Experimental results demonstrate that the proposed method can significantly enhance the quality of the constructed atlas by discovering more anatomical details especially in the highly convoluted cortical regions. The resulting atlas demonstrates superior performance of our atlas when applied to spatially normalizing three different neonatal datasets, compared with other start-of-the-art neonatal brain atlases. PMID:24638883

Technical and Organizational Considerations for the Long-Term Maintenance and Development of Digital Brain Atlases and Web-Based Databases

PubMed Central

Ito, Kei

2010-01-01

Digital brain atlas is a kind of image database that specifically provide information about neurons and glial cells in the brain. It has various advantages that are unmatched by conventional paper-based atlases. Such advantages, however, may become disadvantages if appropriate cares are not taken. Because digital atlases can provide unlimited amount of data, they should be designed to minimize redundancy and keep consistency of the records that may be added incrementally by different staffs. The fact that digital atlases can easily be revised necessitates a system to assure that users can access previous versions that might have been cited in papers at a particular period. To inherit our knowledge to our descendants, such databases should be maintained for a very long period, well over 100 years, like printed books and papers. Technical and organizational measures to enable long-term archive should be considered seriously. Compared to the initial development of the database, subsequent efforts to increase the quality and quantity of its contents are not regarded highly, because such tasks do not materialize in the form of publications. This fact strongly discourages continuous expansion of, and external contributions to, the digital atlases after its initial launch. To solve these problems, the role of the biocurators is vital. Appreciation of the scientific achievements of the people who do not write papers, and establishment of the secure academic career path for them, are indispensable for recruiting talents for this very important job. PMID:20661458

Astronaut Andrew M. Allen looks over procedure book in middeck

NASA Technical Reports Server (NTRS)

1994-01-01

On Columbia's middeck, astronaut Andrew M. Allen, pilot, looks over a procedures book in the midst of a 14-day mission. Allen is attired in a new thermally controlled undergarment. Allen wore the garment during the launch and entry phases of the flight.

Atlas-based system for functional neurosurgery

NASA Astrophysics Data System (ADS)

Nowinski, Wieslaw L.; Yeo, Tseng T.; Yang, Guo L.; Dow, Douglas E.

1997-05-01

This paper addresses the development of an atlas-based system for preoperative functional neurosurgery planning and training, intraoperative support and postoperative analysis. The system is based on Atlas of Stereotaxy of the Human Brain by Schaltenbrand and Wahren used for interactive segmentation and labeling of clinical data in 2D/3D, and for assisting stereotactic targeting. The atlas microseries are digitized, enhanced, segmented, labeled, aligned and organized into mutually preregistered atlas volumes 3D models of the structures are also constructed. The atlas may be interactively registered with the actual patient's data. Several other features are also provided including data reformatting, visualization, navigation, mensuration, and stereotactic path display and editing in 2D/3D. The system increases the accuracy of target definition, reduces the time of planning and time of the procedure itself. It also constitutes a research platform for the construction of more advanced neurosurgery supporting tools and brain atlases.

STS-75 Mission Commander Andrew M. Allen suits up

NASA Technical Reports Server (NTRS)

1996-01-01

STS-75 Mission Commander Andrew M. Allen completes suitup activities in the Operations and Checkout Building. STS-75 will be Allen's third trip into space, his first as commander. Allen and an international crew will depart shortly for Launch Pad 39B, where the Space Shuttle Columbia awaits liftoff during a two-and- a-half-hour launch window opening at 3:18 p.m. EST.

Astronaut Andrew Allen looks over procedure book in middeck

NASA Image and Video Library

1994-03-05

STS062-12-015 (4-18 March 1994) --- On Coumbia's middeck, astronaut Andrew M. Allen, pilot, looks over a procedures book in the midst of a 14-day mission. Allen is attired in a new thermally controlled undergarment. As part of a detailed test objective, both Allen and John H. Casper, mission commander, wore the undergarments during the launch and entry phases of the flight.

A review of Edward Flatau's 1894 Atlas of the Human Brain by the neurologist Sigmund Freud.

PubMed

Triarhou, Lazaros C

2011-01-01

In 1894, the Polish neurologist Edward Flatau (1868-1932), working in Berlin, published an exquisite photographic atlas of the unfixed human brain, preceding by 2 years Das Menschenhirn, the reference work of Gustaf Retzius (1842-1919) in Stockholm. In his early career as a neuroanatomist and neurologist, Sigmund Freud (1856-1939) wrote a review of Flatau's atlas for the Internationale klinische Rundschau, which has not been included in the 'Standard Edition of the Complete Psychological Works'. The aim of the present paper is twofold: to document Freud's review, and to revive the largely forgotten atlas of Flatau. The full text of Freud is presented in translation. Further, one element Flatau, Retzius and Freud had in common is discussed: their early role as protagonists and firm supporters of Ramón y Cajal's neuron theory, the cornerstone of modern neuroscience. Copyright © 2010 S. Karger AG, Basel.

Identification of a set of genes showing regionally enriched expression in the mouse brain

PubMed Central

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa LC; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven JM

2008-01-01

Background The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. Results We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Conclusion Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression. PMID:18625066

Identification of a set of genes showing regionally enriched expression in the mouse brain.

PubMed

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa L C; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven J M

2008-07-14

The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

4D MEMRI atlas of neonatal FVB/N mouse brain development.

PubMed

Szulc, Kamila U; Lerch, Jason P; Nieman, Brian J; Bartelle, Benjamin B; Friedel, Miriam; Suero-Abreu, Giselle A; Watson, Charles; Joyner, Alexandra L; Turnbull, Daniel H

2015-09-01

The widespread use of the mouse as a model system to study brain development has created the need for noninvasive neuroimaging methods that can be applied to early postnatal mice. The goal of this study was to optimize in vivo three- (3D) and four-dimensional (4D) manganese (Mn)-enhanced MRI (MEMRI) approaches for acquiring and analyzing data from the developing mouse brain. The combination of custom, stage-dependent holders and self-gated (motion-correcting) 3D MRI sequences enabled the acquisition of high-resolution (100-μm isotropic), motion artifact-free brain images with a high level of contrast due to Mn-enhancement of numerous brain regions and nuclei. We acquired high-quality longitudinal brain images from two groups of FVB/N strain mice, six mice per group, each mouse imaged on alternate odd or even days (6 3D MEMRI images at each day) covering the developmental stages between postnatal days 1 to 11. The effects of Mn-exposure, anesthesia and MRI were assessed, showing small but significant transient effects on body weight and brain volume, which recovered with time and did not result in significant morphological differences when compared to controls. Metrics derived from deformation-based morphometry (DBM) were used for quantitative analysis of changes in volume and position of a number of brain regions. The cerebellum, a brain region undergoing significant changes in size and patterning at early postnatal stages, was analyzed in detail to demonstrate the spatiotemporal characterization made possible by this new atlas of mouse brain development. These results show that MEMRI is a powerful tool for quantitative analysis of mouse brain development, with great potential for in vivo phenotype analysis in mouse models of neurodevelopmental diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Statistical model of laminar structure for atlas-based segmentation of the fetal brain from in utero MR images

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Kim, Kio; Chandramohan, Dharshan; Rousseau, Francois; Glenn, Orit A.; Studholme, Colin

2009-02-01

Recent advances in MR and image analysis allow for reconstruction of high-resolution 3D images from clinical in utero scans of the human fetal brain. Automated segmentation of tissue types from MR images (MRI) is a key step in the quantitative analysis of brain development. Conventional atlas-based methods for adult brain segmentation are limited in their ability to accurately delineate complex structures of developing tissues from fetal MRI. In this paper, we formulate a novel geometric representation of the fetal brain aimed at capturing the laminar structure of developing anatomy. The proposed model uses a depth-based encoding of tissue occurrence within the fetal brain and provides an additional anatomical constraint in a form of a laminar prior that can be incorporated into conventional atlas-based EM segmentation. Validation experiments are performed using clinical in utero scans of 5 fetal subjects at gestational ages ranging from 20.5 to 22.5 weeks. Experimental results are evaluated against reference manual segmentations and quantified in terms of Dice similarity coefficient (DSC). The study demonstrates that the use of laminar depth-encoded tissue priors improves both the overall accuracy and precision of fetal brain segmentation. Particular refinement is observed in regions of the parietal and occipital lobes where the DSC index is improved from 0.81 to 0.82 for cortical grey matter, from 0.71 to 0.73 for the germinal matrix, and from 0.81 to 0.87 for white matter.

Reply to David Kemmerer's "a critique of Mark D. Allen's 'the preservation of verb subcategory knowledge in a spoken language comprehension deficit'".

PubMed

Allen, Mark D; Owens, Tyler E

2008-07-01

Allen [Allen, M. D. (2005). The preservation of verb subcategory knowledge in a spoken language comprehension deficit. Brain and Language, 95, 255-264] presents evidence from a single patient, WBN, to motivate a theory of lexical processing and representation in which syntactic information may be encoded and retrieved independently of semantic information. In his critique, Kemmerer argues that because Allen depended entirely on preposition-based verb subcategory violations to test WBN's knowledge of correct argument structure, his results, at best, address a "strawman" theory. This argument rests on the assumption that preposition subcategory options are superficial syntactic phenomena which are not represented by argument structure proper. We demonstrate that preposition subcategory is in fact treated as semantically determined argument structure in the theories that Allen evaluated, and thus far from irrelevant. In further discussion of grammatically relevant versus irrelevant semantic features, Kemmerer offers a review of his own studies. However, due to an important design shortcoming in these experiments, we remain unconvinced. Reemphasizing the fact the Allen (2005) never claimed to rule out all semantic contributions to syntax, we propose an improvement in Kemmerer's approach that might provide more satisfactory evidence on the distinction between the kinds of relevant versus irrelevant features his studies have addressed.

33 CFR 80.1440 - Port Allen, Kauai, HI.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Port Allen, Kauai, HI. 80.1440 Section 80.1440 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Pacific Islands § 80.1440 Port Allen, Kauai, HI. A line drawn from...

Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

PubMed Central

Tang, Xiaoying; Yoshida, Shoko; Hsu, John; Huisman, Thierry A. G. M.; Faria, Andreia V.; Oishi, Kenichi; Kutten, Kwame; Poretti, Andrea; Li, Yue; Miller, Michael I.; Mori, Susumu

2014-01-01

In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs). This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases. DTI images are modeled as high dimensional fields, with each voxel exhibiting a vector valued feature comprising of mean diffusivity (MD), fractional anisotropy (FA), and fiber angle. For each structure, the probability distribution of each element in the feature vector is modeled as a mixture of Gaussians, the parameters of which are estimated from the labeled atlases. The structure-specific feature vector is then used to parcellate the test image. For each atlas, a likelihood is iteratively computed based on the structure-specific vector feature. The likelihoods from multiple atlases are then fused. The updating and fusing of the likelihoods is achieved based on the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation problems. We first demonstrate the performance of the algorithm by examining the parcellation accuracy of 18 structures from 25 subjects with a varying degree of structural abnormality. Dice values ranging 0.8–0.9 were obtained. In addition, strong correlation was found between the volume size of the automated and the manual parcellation. Then, we present scan-rescan reproducibility based on another dataset of 16 DTI images – an average of 3.73%, 1.91%, and 1.79% for volume, mean FA, and mean MD respectively. Finally, the range of anatomical variability in the normal population was quantified for each structure. PMID:24809486

Multi-Atlas-Based Attenuation Correction for Brain 18F-FDG PET Imaging Using a Time-of-Flight PET/MR Scanner: Comparison with Clinical Single-Atlas- and CT-Based Attenuation Correction.

PubMed

Sekine, Tetsuro; Burgos, Ninon; Warnock, Geoffrey; Huellner, Martin; Buck, Alfred; Ter Voert, Edwin E G W; Cardoso, M Jorge; Hutton, Brian F; Ourselin, Sebastien; Veit-Haibach, Patrick; Delso, Gaspar

2016-08-01

< 0.01). The errors introduced using either s-Atlas or m-Atlas did not exceed 5% in any brain region investigated. When compared with the clinical s-Atlas, m-Atlas is more accurate, especially in regions close to the skull base. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

UV absorption spectrum of allene radical cations in solid argon

NASA Astrophysics Data System (ADS)

Chin, Chih-Hao; Lin, Meng-Yeh; Huang, Tzu-Ping; Wu, Yu-Jong

2018-05-01

Electron bombardment during deposition of an Ar matrix containing a small proportion of allene generated allene cations. Further irradiation of the matrix sample at 385 nm destroyed the allene cations and formed propyne cations in solid Ar. Both cations were identified according to previously reported IR absorption bands. Using a similar technique, we recorded the ultraviolet absorption spectrum of allene cations in solid Ar. The vibrationally resolved progression recorded in the range of 266-237 nm with intervals of about 800 cm-1 was assigned to the A2E ← X2E transition of allene cations, and the broad continuum absorption recorded in the region of 229-214 nm was assigned to their B2A1 ← X2E transition. These assignments were made based on the observed photolytic behavior of the progressions and the vertical excitation energies and oscillator strengths calculated using time-dependent density functional theory.

Computer Vision Evidence Supporting Craniometric Alignment of Rat Brain Atlases to Streamline Expert-Guided, First-Order Migration of Hypothalamic Spatial Datasets Related to Behavioral Control

PubMed Central

Khan, Arshad M.; Perez, Jose G.; Wells, Claire E.; Fuentes, Olac

2018-01-01

The rat has arguably the most widely studied brain among all animals, with numerous reference atlases for rat brain having been published since 1946. For example, many neuroscientists have used the atlases of Paxinos and Watson (PW, first published in 1982) or Swanson (S, first published in 1992) as guides to probe or map specific rat brain structures and their connections. Despite nearly three decades of contemporaneous publication, no independent attempt has been made to establish a basic framework that allows data mapped in PW to be placed in register with S, or vice versa. Such data migration would allow scientists to accurately contextualize neuroanatomical data mapped exclusively in only one atlas with data mapped in the other. Here, we provide a tool that allows levels from any of the seven published editions of atlases comprising three distinct PW reference spaces to be aligned to atlas levels from any of the four published editions representing S reference space. This alignment is based on registration of the anteroposterior stereotaxic coordinate (z) measured from the skull landmark, Bregma (β). Atlas level alignments performed along the z axis using one-dimensional Cleveland dot plots were in general agreement with alignments obtained independently using a custom-made computer vision application that utilized the scale-invariant feature transform (SIFT) and Random Sample Consensus (RANSAC) operation to compare regions of interest in photomicrographs of Nissl-stained tissue sections from the PW and S reference spaces. We show that z-aligned point source data (unpublished hypothalamic microinjection sites) can be migrated from PW to S space to a first-order approximation in the mediolateral and dorsoventral dimensions using anisotropic scaling of the vector-formatted atlas templates, together with expert-guided relocation of obvious outliers in the migrated datasets. The migrated data can be contextualized with other datasets mapped in S space, including

Mission Specialist (MS) Allen experiments with beverage on middeck

NASA Technical Reports Server (NTRS)

1982-01-01

Mission Specialist (MS) Allen, using beverage container and drinking straw, experiments with microgravity chararcteristics of orange juice on middeck in front of the Development Flight Instrument (DFI) unit and forward lockers. Allen laughes as he watches the results of his experimentation.

Exploiting [2+2] cycloaddition chemistry: achievements with allenes.

PubMed

Alcaide, Benito; Almendros, Pedro; Aragoncillo, Cristina

2010-02-01

The allene moiety represents an excellent partner for the [2+2] cycloaddition with alkenes and alkynes, affording the cyclobutane and cyclobutene skeletons in a single step. This strategy has been widely studied under thermal, photochemical and microwave induced conditions. More recently, the use of transition metal catalysis has been introduced as an alternative relying on the activation of the allenic component. On the other hand, the intramolecular version has attracted much attention as a strategy for the synthesis of polycyclic compounds in a regio- and stereoselective fashion. This critical review focuses on the most recently developed [2+2] cycloadditions on allenes along with remarkable early works accounting for the mechanism, the regio- and diastereoselectivity of the cycloadducts formed (103 references).

AICHA: An atlas of intrinsic connectivity of homotopic areas.

PubMed

Joliot, Marc; Jobard, Gaël; Naveau, Mikaël; Delcroix, Nicolas; Petit, Laurent; Zago, Laure; Crivello, Fabrice; Mellet, Emmanuel; Mazoyer, Bernard; Tzourio-Mazoyer, Nathalie

2015-10-30

Atlases of brain anatomical ROIs are widely used for functional MRI data analysis. Recently, it was proposed that an atlas of ROIs derived from a functional brain parcellation could be advantageous, in particular for understanding how different regions share information. However, functional atlases so far proposed do not account for a crucial aspect of cerebral organization, namely homotopy, i.e. that each region in one hemisphere has a homologue in the other hemisphere. We present AICHA (for Atlas of Intrinsic Connectivity of Homotopic Areas), a functional brain ROIs atlas based on resting-state fMRI data acquired in 281 individuals. AICHA ROIs cover the whole cerebrum, each having 1-homogeneity of its constituting voxels intrinsic activity, and 2-a unique homotopic contralateral counterpart with which it has maximal intrinsic connectivity. AICHA was built in 4 steps: (1) estimation of resting-state networks (RSNs) using individual resting-state fMRI independent components, (2) k-means clustering of voxel-wise group level profiles of connectivity, (3) homotopic regional grouping based on maximal inter-hemispheric functional correlation, and (4) ROI labeling. AICHA includes 192 homotopic region pairs (122 gyral, 50 sulcal, and 20 gray nuclei). As an application, we report inter-hemispheric (homotopic and heterotopic) and intra-hemispheric connectivity patterns at different sparsities. ROI functional homogeneity was higher for AICHA than for anatomical ROI atlases, but slightly lower than for another functional ROI atlas not accounting for homotopy. AICHA is ideally suited for intrinsic/effective connectivity analyses, as well as for investigating brain hemispheric specialization. Copyright © 2015 Elsevier B.V. All rights reserved.

Electrons in the Inner Van Allen Belt

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reeves, Geoff

A recent study shows that the inner Van Allen belt has less radiation than previously believed. Observations from NASA’s Van Allen probes show the fastest, most energetic electrons in the inner radiation belt are actually much rarer and harder to find than scientists expected. This is good news for spacecraft that are orbiting in the region and can be damaged by high levels of radiation. The results will also help scientists better understand—and detect—effects from high-altitude nuclear explosions.

Automated diagnosis of Alzheimer's disease with multi-atlas based whole brain segmentations

NASA Astrophysics Data System (ADS)

Luo, Yuan; Tang, Xiaoying

2017-03-01

Voxel-based analysis is widely used in quantitative analysis of structural brain magnetic resonance imaging (MRI) and automated disease detection, such as Alzheimer's disease (AD). However, noise at the voxel level may cause low sensitivity to AD-induced structural abnormalities. This can be addressed with the use of a whole brain structural segmentation approach which greatly reduces the dimension of features (the number of voxels). In this paper, we propose an automatic AD diagnosis system that combines such whole brain segmen- tations with advanced machine learning methods. We used a multi-atlas segmentation technique to parcellate T1-weighted images into 54 distinct brain regions and extract their structural volumes to serve as the features for principal-component-analysis-based dimension reduction and support-vector-machine-based classification. The relationship between the number of retained principal components (PCs) and the diagnosis accuracy was systematically evaluated, in a leave-one-out fashion, based on 28 AD subjects and 23 age-matched healthy subjects. Our approach yielded pretty good classification results with 96.08% overall accuracy being achieved using the three foremost PCs. In addition, our approach yielded 96.43% specificity, 100% sensitivity, and 0.9891 area under the receiver operating characteristic curve.

The Cerefy Neuroradiology Atlas: a Talairach-Tournoux atlas-based tool for analysis of neuroimages available over the internet.

PubMed

Nowinski, Wieslaw L; Belov, Dmitry

2003-09-01

The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.

A cross-validated cytoarchitectonic atlas of the human ventral visual stream.

PubMed

Rosenke, Mona; Weiner, Kevin S; Barnett, Michael A; Zilles, Karl; Amunts, Katrin; Goebel, Rainer; Grill-Spector, Kalanit

2018-04-15

The human ventral visual stream consists of several areas that are considered processing stages essential for perception and recognition. A fundamental microanatomical feature differentiating areas is cytoarchitecture, which refers to the distribution, size, and density of cells across cortical layers. Because cytoarchitectonic structure is measured in 20-micron-thick histological slices of postmortem tissue, it is difficult to assess (a) how anatomically consistent these areas are across brains and (b) how they relate to brain parcellations obtained with prevalent neuroimaging methods, acquired at the millimeter and centimeter scale. Therefore, the goal of this study was to (a) generate a cross-validated cytoarchitectonic atlas of the human ventral visual stream on a whole brain template that is commonly used in neuroimaging studies and (b) to compare this atlas to a recently published retinotopic parcellation of visual cortex (Wang et al., 2014). To achieve this goal, we generated an atlas of eight cytoarchitectonic areas: four areas in the occipital lobe (hOc1-hOc4v) and four in the fusiform gyrus (FG1-FG4), then we tested how the different alignment techniques affect the accuracy of the resulting atlas. Results show that both cortex-based alignment (CBA) and nonlinear volumetric alignment (NVA) generate an atlas with better cross-validation performance than affine volumetric alignment (AVA). Additionally, CBA outperformed NVA in 6/8 of the cytoarchitectonic areas. Finally, the comparison of the cytoarchitectonic atlas to a retinotopic atlas shows a clear correspondence between cytoarchitectonic and retinotopic areas in the ventral visual stream. The successful performance of CBA suggests a coupling between cytoarchitectonic areas and macroanatomical landmarks in the human ventral visual stream, and furthermore, that this coupling can be utilized for generating an accurate group atlas. In addition, the coupling between cytoarchitecture and retinotopy highlights

Discriminative confidence estimation for probabilistic multi-atlas label fusion.

PubMed

Benkarim, Oualid M; Piella, Gemma; González Ballester, Miguel Angel; Sanroma, Gerard

2017-12-01

Quantitative neuroimaging analyses often rely on the accurate segmentation of anatomical brain structures. In contrast to manual segmentation, automatic methods offer reproducible outputs and provide scalability to study large databases. Among existing approaches, multi-atlas segmentation has recently shown to yield state-of-the-art performance in automatic segmentation of brain images. It consists in propagating the labelmaps from a set of atlases to the anatomy of a target image using image registration, and then fusing these multiple warped labelmaps into a consensus segmentation on the target image. Accurately estimating the contribution of each atlas labelmap to the final segmentation is a critical step for the success of multi-atlas segmentation. Common approaches to label fusion either rely on local patch similarity, probabilistic statistical frameworks or a combination of both. In this work, we propose a probabilistic label fusion framework based on atlas label confidences computed at each voxel of the structure of interest. Maximum likelihood atlas confidences are estimated using a supervised approach, explicitly modeling the relationship between local image appearances and segmentation errors produced by each of the atlases. We evaluate different spatial pooling strategies for modeling local segmentation errors. We also present a novel type of label-dependent appearance features based on atlas labelmaps that are used during confidence estimation to increase the accuracy of our label fusion. Our approach is evaluated on the segmentation of seven subcortical brain structures from the MICCAI 2013 SATA Challenge dataset and the hippocampi from the ADNI dataset. Overall, our results indicate that the proposed label fusion framework achieves superior performance to state-of-the-art approaches in the majority of the evaluated brain structures and shows more robustness to registration errors. Copyright © 2017 Elsevier B.V. All rights reserved.

High-Throughput Analysis of Dynamic Gene Expression Associated with Sleep Deprivation and Recovery Sleep in the Mouse Brain

DTIC Science & Technology

2006-12-01

CONTRACTING ORGANIZATION : Allen Institute for Brain Science Seattle, WA 98103 REPORT DATE...5e. TASK NUMBER Email: edl@alleninstitute.org 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING... ORGANIZATION REPORT NUMBER Allen Institute for Brain Science Seattle, WA 98103 9. SPONSORING / MONITORING AGENCY NAME(S) AND

Allen Auditorium attic looking from southeast corner. Wine barrels with ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Allen Auditorium attic looking from southeast corner. Wine barrels with scrap used for counterweight material for lift up walls no longer in use - Sheldon Jackson College, Richard H. Allen Memorial Hall, Lincoln Street, Sitka, Sitka Borough, AK

Mapping heritability and molecular genetic associations with cortical features using probabilistic brain atlases: methods and applications to schizophrenia.

PubMed

Cannon, Tyrone D; Thompson, Paul M; van Erp, Theo G M; Huttunen, Matti; Lonnqvist, Jouko; Kaprio, Jaakko; Toga, Arthur W

2006-01-01

There is an urgent need to decipher the complex nature of genotype-phenotype relationships within the multiple dimensions of brain structure and function that are compromised in neuropsychiatric syndromes such as schizophrenia. Doing so requires sophisticated methodologies to represent population variability in neural traits and to probe their heritable and molecular genetic bases. We have recently developed and applied computational algorithms to map the heritability of, as well as genetic linkage and association to, neural features encoded using brain imaging in the context of three-dimensional (3D), populationbased, statistical brain atlases. One set of algorithms builds on our prior work using classical twin study methods to estimate heritability by fitting biometrical models for additive genetic, unique, and common environmental influences. Another set of algorithms performs regression-based (Haseman-Elston) identical-bydescent linkage analysis and genetic association analysis of DNA polymorphisms in relation to neural traits of interest in the same 3D population-based brain atlas format. We demonstrate these approaches using samples of healthy monozygotic (MZ) and dizygotic (DZ) twin pairs, as well as MZ and DZ twin pairs discordant for schizophrenia, but the methods can be generalized to other classes of relatives and to other diseases. The results confirm prior evidence of genetic influences on gray matter density in frontal brain regions. They also provide converging evidence that the chromosome 1q42 region is relevant to schizophrenia by demonstrating linkage and association of markers of the Transelin-Associated-Factor-X and Disrupted-In- Schizophrenia-1 genes with prefrontal cortical gray matter deficits in twins discordant for schizophrenia.

Astronauts Allen and Gemar during Extravehicular activity training in CCT

NASA Image and Video Library

1993-10-13

Astronauts Charles D. (Sam) Gemar, and Andrew M. Allen participate in a training exercise at JSC's Crew Compartment Trainer (CCT), located in the Shuttle mockup and integration laboratory. Gemar sits inside the airlock as Allen reviews procedures for EVA.

Quantitative Evaluation of Atlas-based Attenuation Correction for Brain PET in an Integrated Time-of-Flight PET/MR Imaging System.

PubMed

Yang, Jaewon; Jian, Yiqiang; Jenkins, Nathaniel; Behr, Spencer C; Hope, Thomas A; Larson, Peder E Z; Vigneron, Daniel; Seo, Youngho

2017-07-01

Purpose To assess the patient-dependent accuracy of atlas-based attenuation correction (ATAC) for brain positron emission tomography (PET) in an integrated time-of-flight (TOF) PET/magnetic resonance (MR) imaging system. Materials and Methods Thirty recruited patients provided informed consent in this institutional review board-approved study. All patients underwent whole-body fluorodeoxyglucose PET/computed tomography (CT) followed by TOF PET/MR imaging. With use of TOF PET data, PET images were reconstructed with four different attenuation correction (AC) methods: PET with patient CT-based AC (CTAC), PET with ATAC (air and bone from an atlas), PET with ATAC patientBone (air and tissue from the atlas with patient bone), and PET with ATAC boneless (air and tissue from the atlas without bone). For quantitative evaluation, PET mean activity concentration values were measured in 14 1-mL volumes of interest (VOIs) distributed throughout the brain and statistical significance was tested with a paired t test. Results The mean overall difference (±standard deviation) of PET with ATAC compared with PET with CTAC was -0.69 kBq/mL ± 0.60 (-4.0% ± 3.2) (P < .001). The results were patient dependent (range, -9.3% to 0.57%) and VOI dependent (range, -5.9 to -2.2). In addition, when bone was not included for AC, the overall difference of PET with ATAC boneless (-9.4% ± 3.7) was significantly worse than that of PET with ATAC (-4.0% ± 3.2) (P < .001). Finally, when patient bone was used for AC instead of atlas bone, the overall difference of PET with ATAC patientBone (-1.5% ± 1.5) improved over that of PET with ATAC (-4.0% ± 3.2) (P < .001). Conclusion ATAC in PET/MR imaging achieves similar quantification accuracy to that from CTAC by means of atlas-based bone compensation. However, patient-specific anatomic differences from the atlas causes bone attenuation differences and misclassified sinuses, which result in patient-dependent performance variation of ATAC. © RSNA

Mission Specialist (MS) Allen experiments with beverage on middeck

NASA Image and Video Library

1982-11-16

STS005-04-134 (11-16 Nov. 1982) --- Astronaut Joseph P. Allen IV, STS-5 mission specialist, uses beverage container and drinking straw, experiments with microgravity characteristics of orange juice on middeck in front of the Development Flight Instrument (DFI) unit and forward lockers. Allen laughs as he watches the results of his experimentation. Photo credit: NASA

The Gift of Writing: An Interview with Janet Allen

ERIC Educational Resources Information Center

Lesesne, Teri S.

2005-01-01

Janet Allen cares passionately about books and reading and that passion shines in her presentation. When she had her first foray into children's literature, it was expected that she would have a great deal to say to educators about writing and reading. In this article, an interview with the author is presented. Allen talks about how her experience…

Warping an atlas derived from serial histology to 5 high-resolution MRIs.

PubMed

Tullo, Stephanie; Devenyi, Gabriel A; Patel, Raihaan; Park, Min Tae M; Collins, D Louis; Chakravarty, M Mallar

2018-06-19

Previous work from our group demonstrated the use of multiple input atlases to a modified multi-atlas framework (MAGeT-Brain) to improve subject-based segmentation accuracy. Currently, segmentation of the striatum, globus pallidus and thalamus are generated from a single high-resolution and -contrast MRI atlas derived from annotated serial histological sections. Here, we warp this atlas to five high-resolution MRI templates to create five de novo atlases. The overall goal of this work is to use these newly warped atlases as input to MAGeT-Brain in an effort to consolidate and improve the workflow presented in previous manuscripts from our group, allowing for simultaneous multi-structure segmentation. The work presented details the methodology used for the creation of the atlases using a technique previously proposed, where atlas labels are modified to mimic the intensity and contrast profile of MRI to facilitate atlas-to-template nonlinear transformation estimation. Dice's Kappa metric was used to demonstrate high quality registration and segmentation accuracy of the atlases. The final atlases are available at https://github.com/CobraLab/atlases/tree/master/5-atlas-subcortical.

New Results About the Earth’s Van Allen Radiation Belts

NASA Astrophysics Data System (ADS)

Baker, Daniel

2015-01-01

The first great scientific discovery of the Space Age was that the Earth is enshrouded in toroids, or 'belts', of very high-energy magnetically trapped charged particles. Early observations of the radiation environment clearly indicated that the Van Allen belts could be delineated into an inner zone dominated by high-energy protons and an outer zone dominated by high-energy electrons. Subsequent studies showed that electrons in the energy range 100 keV < E< 1 MeV often populated both the inner and outer zones with a pronounced 'slot' region relatively devoid of energetic electrons existing between them. This two-belt structure for the Van Allen moderate-energy electron component was explained as being due to strong interactions of electrons with electromagnetic waves just inside the cold plasma (plasmapause) boundary. The energy distribution, spatial extent and particle species makeup of the Van Allen belts has been subsequently explored by several space missions. However, recent observations by the NASA dual-spacecraft Van Allen Probes mission have revealed wholly unexpected properties of the radiation belts, especially at highly relativistic (E > 2 MeV) and ultra-relativistic (E > 5 MeV) kinetic energies. In this presentation we show using high spatial and temporal resolution data from the Relativistic Electron-Proton Telescope (REPT) experiment on board the Van Allen Probes that multiple belts can exist concurrently and that an exceedingly sharp inner boundary exists for ultra-relativistic electrons. Using additionally available Van Allen Probes data, we demonstrate that these remarkable features of energetic electrons are not due to a physical boundary within Earth's intrinsic magnetic field. Neither is it likely that human-generated electromagnetic transmitter wave fields might produce such effects. Rather, we conclude from these unique measurements that slow natural inward radial diffusion combined with weak, but persistent, wave-particle pitch angle

Global differential expression of genes located in the Down Syndrome Critical Region in normal human brain

PubMed Central

Montoya, Julio Cesar; Fajardo, Dianora; Peña, Angela; Sánchez, Adalberto; Domínguez, Martha C; Satizábal, José María

2014-01-01

Background: The information of gene expression obtained from databases, have made possible the extraction and analysis of data related with several molecular processes involving not only in brain homeostasis but its disruption in some neuropathologies; principally in Down syndrome and the Alzheimer disease. Objective: To correlate the levels of transcription of 19 genes located in the Down Syndrome Critical Region (DSCR) with their expression in several substructures of normal human brain. Methods: There were obtained expression profiles of 19 DSCR genes in 42 brain substructures, from gene expression values available at the database of the human brain of the Brain Atlas of the Allen Institute for Brain Sciences", (http://human.brain-map.org/). The co-expression patterns of DSCR genes in brain were calculated by using multivariate statistical methods. Results: Highest levels of gene expression were registered at caudate nucleus, nucleus accumbens and putamen among central areas of cerebral cortex. Increased expression levels of RCAN1 that encode by a protein involved in signal transduction process of the CNS were recorded for PCP4 that participates in the binding to calmodulin and TTC3; a protein that is associated with differentiation of neurons. That previously identified brain structures play a crucial role in the learning process, in different class of memory and in motor skills. Conclusion: The precise regulation of DSCR gene expression is crucial to maintain the brain homeostasis, especially in those areas with high levels of gene expression associated with a remarkable process of learning and cognition. PMID:25767303

NASA's Van Allen Probes Discover a Surprise Circling Earth

NASA Image and Video Library

2017-12-08

Two giant swaths of radiation, known as the Van Allen Belts, surrounding Earth were discovered in 1958. In 2012, observations from the Van Allen Probes showed that a third belt can sometimes appear. The radiation is shown here in yellow, with green representing the spaces between the belts. Credit: NASA/Van Allen Probes/Goddard Space Flight Center To read more go to: www.nasa.gov/mission_pages/rbsp/news/third-belt.html NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Astronauts Allen and Gemar during extravehicular activity (EVA) training in CCT

NASA Technical Reports Server (NTRS)

1994-01-01

Astronauts Charles D. (Sam) Gemar, and Andrew M. Allen participate in a training exercise at JSC's Crew Compartment Trainer (CCT), located in the Space Vehicle Mockup Facility. Gemar sits inside the airlock as Allen reviews procedures for EVA.

Water resources of Allen Parish

USGS Publications Warehouse

Prakken, Lawrence B.; Griffith, Jason M.; Fendick, Robert B.

2012-01-01

In 2005, approximately 29.2 million gallons per day (Mgal/d) of water were withdrawn in Allen Parish, Louisiana, including about 26.8 Mgal/d from groundwater sources and 2.45 Mgal/d from surface-water sources. Rice irrigation accounted for 74 percent (21.7 Mgal/d) of the total water withdrawn. Other categories of use included public supply, industrial, rural domestic, livestock, general irrigation, and aquaculture. Water-use data collected at 5-year intervals from 1960 to 2005 indicate water withdrawals in the parish were greatest in 1960 (119 Mgal/d) and 1980 (98.7 Mgal/d). The substantial decrease in surface-water use between 1960 and 1965 is primarily attributable to rice-irrigation withdrawals declining from 61.2 to 6.74 Mgal/d. This fact sheet summarizes information on the water resources of Allen Parish, La. Information on groundwater and surface-water availability, quality, development, use, and trends is based on previously published reports listed in the Selected References section.

Regional expression of the MAPT gene is associated with loss of hubs in brain networks and cognitive impairment in Parkinson disease and progressive supranuclear palsy.

PubMed

Rittman, Timothy; Rubinov, Mikail; Vértes, Petra E; Patel, Ameera X; Ginestet, Cedric E; Ghosh, Boyd C P; Barker, Roger A; Spillantini, Maria Grazia; Bullmore, Edward T; Rowe, James B

2016-12-01

Abnormalities of tau protein are central to the pathogenesis of progressive supranuclear palsy, whereas haplotype variation of the tau gene MAPT influences the risk of Parkinson disease and Parkinson's disease dementia. We assessed whether regional MAPT expression might be associated with selective vulnerability of global brain networks to neurodegenerative pathology. Using task-free functional magnetic resonance imaging in progressive supranuclear palsy, Parkinson disease, and healthy subjects (n = 128), we examined functional brain networks and measured the connection strength between 471 gray matter regions. We obtained MAPT and SNCA microarray expression data in healthy subjects from the Allen brain atlas. Regional connectivity varied according to the normal expression of MAPT. The regional expression of MAPT correlated with the proportionate loss of regional connectivity in Parkinson's disease. Executive cognition was impaired in proportion to the loss of hub connectivity. These effects were not seen with SNCA, suggesting that alpha-synuclein pathology is not mediated through global network properties. The results establish a link between regional MAPT expression and selective vulnerability of functional brain networks to neurodegeneration. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Self-correcting multi-atlas segmentation

NASA Astrophysics Data System (ADS)

Gao, Yi; Wilford, Andrew; Guo, Liang

2016-03-01

In multi-atlas segmentation, one typically registers several atlases to the new image, and their respective segmented label images are transformed and fused to form the final segmentation. After each registration, the quality of the registration is reflected by the single global value: the final registration cost. Ideally, if the quality of the registration can be evaluated at each point, independent of the registration process, which also provides a direction in which the deformation can further be improved, the overall segmentation performance can be improved. We propose such a self-correcting multi-atlas segmentation method. The method is applied on hippocampus segmentation from brain images and statistically significantly improvement is observed.

Automatic testing and assessment of neuroanatomy using a digital brain atlas: method and development of computer- and mobile-based applications.

PubMed

Nowinski, Wieslaw L; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G; Marchenko, Yevgen; Volkau, Ihar

2009-10-01

Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to Terminologia Anatomica. Because the cerebral models are fully segmented and labeled, our approach enables automatic and random atlas-derived generation of questions to test location and naming of cerebral structures. This is done in four steps: test individualization by the instructor, test taking by the students at their convenience, automatic student assessment by the application, and communication of the individual assessment to the instructor. A computer-based application with an interactive 3D atlas and a preliminary mobile-based application were developed to realize this approach. The application works in two test modes: instructor and student. In the instructor mode, the instructor customizes the test by setting the scope of testing and student performance criteria, which takes a few seconds. In the student mode, the student is tested and automatically assessed. Self-testing is also feasible at any time and pace. Our approach is automatic both with respect to test generation and student assessment. It is also objective, rapid, and customizable. We believe that this approach is novel from computer-based, mobile-based, and atlas-assisted standpoints.

An Allenic Pauson–Khand Approach to 6,12-Guaianolides

PubMed Central

Grillet, Francois; Huang, Chaofeng

2011-01-01

Cyclocarbonylation of α-methylene butyrolactone-containing allene-ynes affords 6,12-guaianolide ring systems. Incorporation of the α-methylene butyrolactone early in a synthetic sequence is rare for reactivity reasons; however, this moiety proves to be beneficial to the allenic Pauson−Khand reaction. The three double bonds and the ketone in the resulting 5-7-5 ring system bear significant differences in their reactivity and are ideally positioned for synthetic application to 6,12-guaianolides and analogs. PMID:22070869

An allenic Pauson-Khand approach to 6,12-guaianolides.

PubMed

Grillet, Francois; Huang, Chaofeng; Brummond, Kay M

2011-12-02

Cyclocarbonylation of α-methylene butyrolactone-containing allene-ynes affords 6,12-guaianolide ring systems. Incorporation of the α-methylene butyrolactone early in a synthetic sequence is rare for reactivity reasons; however, this moiety proves to be beneficial to the allenic Pauson-Khand reaction. The three double bonds and the ketone in the resulting 5-7-5 ring system bear significant differences in their reactivity and are ideally positioned for synthetic application to 6,12-guaianolides and analogs.

Generation and evaluation of an ultra-high-field atlas with applications in DBS planning

NASA Astrophysics Data System (ADS)

Wang, Brian T.; Poirier, Stefan; Guo, Ting; Parrent, Andrew G.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Purpose Deep brain stimulation (DBS) is a common treatment for Parkinson's disease (PD) and involves the use of brain atlases or intrinsic landmarks to estimate the location of target deep brain structures, such as the subthalamic nucleus (STN) and the globus pallidus pars interna (GPi). However, these structures can be difficult to localize with conventional clinical magnetic resonance imaging (MRI), and thus targeting can be prone to error. Ultra-high-field imaging at 7T has the ability to clearly resolve these structures and thus atlases built with these data have the potential to improve targeting accuracy. Methods T1 and T2-weighted images of 12 healthy control subjects were acquired using a 7T MR scanner. These images were then used with groupwise registration to generate an unbiased average template with T1w and T2w contrast. Deep brain structures were manually labelled in each subject by two raters and rater reliability was assessed. We compared the use of this unbiased atlas with two other methods of atlas-based segmentation (single-template and multi-template) for subthalamic nucleus (STN) segmentation on 7T MRI data. We also applied this atlas to clinical DBS data acquired at 1.5T to evaluate its efficacy for DBS target localization as compared to using a standard atlas. Results The unbiased templates provide superb detail of subcortical structures. Through one-way ANOVA tests, the unbiased template is significantly (p <0.05) more accurate than a single-template in atlas-based segmentation and DBS target localization tasks. Conclusion The generated unbiased averaged templates provide better visualization of deep brain nuclei and an increase in accuracy over single-template and lower field strength atlases.

Global solution branches for a nonlocal Allen-Cahn equation

NASA Astrophysics Data System (ADS)

Kuto, Kousuke; Mori, Tatsuki; Tsujikawa, Tohru; Yotsutani, Shoji

2018-05-01

We consider the Neumann problem of a 1D stationary Allen-Cahn equation with nonlocal term. Our previous paper [4] obtained a local branch of asymmetric solutions which bifurcates from a point on the branch of odd-symmetric solutions. This paper derives the global behavior of the branch of asymmetric solutions, and moreover, determines the set of all solutions to the nonlocal Allen-Cahn equation. Our proof is based on a level set analysis for an integral map associated with the nonlocal term.

Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

NASA Astrophysics Data System (ADS)

Liu, Mengyuan; Seshamani, Sharmishtaa; Harrylock, Lisa; Kitsch, Averi; Miller, Steven; Chau, Van; Poskitt, Kenneth; Rousseau, Francois; Studholme, Colin

2014-03-01

One of the most common approaches to MRI brain tissue segmentation is to employ an atlas prior to initialize an Expectation- Maximization (EM) image labeling scheme using a statistical model of MRI intensities. This prior is commonly derived from a set of manually segmented training data from the population of interest. However, in cases where subject anatomy varies significantly from the prior anatomical average model (for example in the case where extreme developmental abnormalities or brain injuries occur), the prior tissue map does not provide adequate information about the observed MRI intensities to ensure the EM algorithm converges to an anatomically accurate labeling of the MRI. In this paper, we present a novel approach for automatic segmentation of such cases. This approach augments the atlas-based EM segmentation by exploring methods to build a hybrid tissue segmentation scheme that seeks to learn where an atlas prior fails (due to inadequate representation of anatomical variation in the statistical atlas) and utilize an alternative prior derived from a patch driven search of the atlas data. We describe a framework for incorporating this patch-based augmentation of EM (PBAEM) into a 4D age-specific atlas-based segmentation of developing brain anatomy. The proposed approach was evaluated on a set of MRI brain scans of premature neonates with ages ranging from 27.29 to 46.43 gestational weeks (GWs). Results indicated superior performance compared to the conventional atlas-based segmentation method, providing improved segmentation accuracy for gray matter, white matter, ventricles and sulcal CSF regions.

Atlas warping for brain morphometry

NASA Astrophysics Data System (ADS)

Machado, Alexei M. C.; Gee, James C.

1998-06-01

In this work, we describe an automated approach to morphometry based on spatial normalizations of the data, and demonstrate its application to the analysis of gender differences in the human corpus callosum. The purpose is to describe a population by a reduced and representative set of variables, from which a prior model can be constructed. Our approach is rooted in the assumption that individual anatomies can be considered as quantitative variations on a common underlying qualitative plane. We can therefore imagine that a given individual's anatomy is a warped version of some referential anatomy, also known as an atlas. The spatial warps which transform a labeled atlas into anatomic alignment with a population yield immediate knowledge about organ size and shape in the group. Furthermore, variation within the set of spatial warps is directly related to the anatomic variation among the subjects. Specifically, the shape statistics--mean and variance of the mappings--for the population can be calculated in a special basis, and an eigendecomposition of the variance performed to identify the most significant modes of shape variation. The results obtained with the corpus callosum study confirm the existence of substantial anatomical differences between males and females, as reported in previous experimental work.

Spacecraft-level verification of the Van Allen Probes' RF communication system

NASA Astrophysics Data System (ADS)

Crowne, M. J.; Srinivasan, D.; Royster, D.; Weaver, G.; Matlin, D.; Mosavi, N.

This paper presents the verification process, lessons learned, and selected test results of the radio frequency (RF) communication system of the Van Allen Probes, formerly known as the Radiation Belt Storm Probes (RBSP). The Van Allen Probes mission is investigating the doughnut-shaped regions of space known as the Van Allen radiation belts where the Sun interacts with charged particles trapped in Earth's magnetic field. Understanding this dynamic area that surrounds our planet is important to improving our ability to design spacecraft and missions for reliability and astronaut safety. The Van Allen Probes mission features two nearly identical spacecraft designed, built, and operated by the Johns Hopkins University Applied Physics Laboratory (JHU/APL) for the National Aeronautics and Space Administration (NASA). The RF communication system features the JHU/APL Frontier Radio. The Frontier Radio is a software-defined radio (SDR) designed for spaceborne communications, navigation, radio science, and sensor applications. This mission marks the first spaceflight usage of the Frontier Radio. RF ground support equipment (RF GSE) was developed using a ground station receiver similar to what will be used in flight and whose capabilities provided clarity into RF system performance that was previously not obtained until compatibility testing with the ground segments. The Van Allen Probes underwent EMC, acoustic, vibration, and thermal vacuum testing at the environmental test facilities at APL. During this time the RF communication system was rigorously tested to ensure optimal performance, including system-level testing down to threshold power levels. Compatibility tests were performed with the JHU/APL Satellite Communication Facility (SCF), the Universal Space Network (USN), and the Tracking and Data Relay Satellite System (TDRSS). Successful completion of this program as described in this paper validated the design of the system and demonstrated that it will be able to me

Q & A with Ed Tech Leaders: Interview with Michael W. Allen

ERIC Educational Resources Information Center

Shaughnessy, Michael F.

2014-01-01

Michael W. Allen, the Chairman and CEO of Allen Interactions, is an architect of interactive multimedia learning and is recognized for his many insights, inventions, and presentations. With over 50 years of experience in e-learning, both in academic and corporate settings, he is known for his role in creating Authorware and overseeing the work of…

Particle Energization in Earth's Van Allen Radiation Belts Due to Solar Wind Forcing

NASA Astrophysics Data System (ADS)

Baker, D. N.

2017-12-01

Early observations of the Earth's radiation environment clearly indicated that the Van Allen belts could be delineated into an inner zone dominated by high-energy protons and an outer zone dominated by high-energy electrons. The energy distribution, spatial extent and particle species makeup of the Van Allen belts has been subsequently explored by several space missions. However, recent observations by the NASA dual-spacecraft Van Allen Probes mission have revealed unexpected properties of the radiation belts, especially for electrons at highly relativistic (E > 2 MeV) and ultra-relativistic (E > 5 MeV) kinetic energies. In this presentation we show using high spatial and temporal resolution data from the experiments on board the Van Allen Probes that multiple belts can exist concurrently and that an exceedingly sharp inner boundary exists for ultra-relativistic electrons. Using additionally available Van Allen Probes data, we demonstrate that these remarkable features of energetic electrons are driven by strong solar and solar wind forcings. The comprehensive Van Allen Probes data show more broadly and in many ways how extremely high energy particles are accelerated, transported, and lost in the magnetosphere due to interplanetary shock wave interactions, coronal mass ejection impacts, and high-speed solar wind streams. The new data have shown especially how dayside processes play a key role in electron acceleration and loss processes.

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

NASA Astrophysics Data System (ADS)

Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.

2017-04-01

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

Construction of 4D high-definition cortical surface atlases of infants: Methods and applications.

PubMed

Li, Gang; Wang, Li; Shi, Feng; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-10-01

In neuroimaging, cortical surface atlases play a fundamental role for spatial normalization, analysis, visualization, and comparison of results across individuals and different studies. However, existing cortical surface atlases created for adults are not suitable for infant brains during the first two postnatal years, which is the most dynamic period of postnatal structural and functional development of the highly-folded cerebral cortex. Therefore, spatiotemporal cortical surface atlases for infant brains are highly desired yet still lacking for accurate mapping of early dynamic brain development. To bridge this significant gap, leveraging our infant-dedicated computational pipeline for cortical surface-based analysis and the unique longitudinal infant MRI dataset acquired in our research center, in this paper, we construct the first spatiotemporal (4D) high-definition cortical surface atlases for the dynamic developing infant cortical structures at seven time points, including 1, 3, 6, 9, 12, 18, and 24 months of age, based on 202 serial MRI scans from 35 healthy infants. For this purpose, we develop a novel method to ensure the longitudinal consistency and unbiasedness to any specific subject and age in our 4D infant cortical surface atlases. Specifically, we first compute the within-subject mean cortical folding by unbiased groupwise registration of longitudinal cortical surfaces of each infant. Then we establish longitudinally-consistent and unbiased inter-subject cortical correspondences by groupwise registration of the geometric features of within-subject mean cortical folding across all infants. Our 4D surface atlases capture both longitudinally-consistent dynamic mean shape changes and the individual variability of cortical folding during early brain development. Experimental results on two independent infant MRI datasets show that using our 4D infant cortical surface atlases as templates leads to significantly improved accuracy for spatial normalization

Clarence Allen talks about the responsibilities in earthquake prediction

USGS Publications Warehouse

Spall, H.

1978-01-01

Dr. Clarence R. Allen is professor of geology and geophysics at the California Institute of Technology. He has been a member of advisory panels to the Executive Office of the President, National Academy of Sciences, National Science Foundation, U.S Geological Survey, UNESCO, California State Mining and Geology Board, and the California Department of Water Resources. Dr. Allen has been President of both the Geological Society of America and the Seismological Society of America (SSA). The title of this interview is based on his presidential address to the SSA in 1976. 

Repeatability of Brain Volume Measurements Made with the Atlas-based Method from T1-weighted Images Acquired Using a 0.4 Tesla Low Field MR Scanner.

PubMed

Goto, Masami; Suzuki, Makoto; Mizukami, Shinya; Abe, Osamu; Aoki, Shigeki; Miyati, Tosiaki; Fukuda, Michinari; Gomi, Tsutomu; Takeda, Tohoru

2016-10-11

An understanding of the repeatability of measured results is important for both the atlas-based and voxel-based morphometry (VBM) methods of magnetic resonance (MR) brain volumetry. However, many recent studies that have investigated the repeatability of brain volume measurements have been performed using static magnetic fields of 1-4 tesla, and no study has used a low-strength static magnetic field. The aim of this study was to investigate the repeatability of measured volumes using the atlas-based method and a low-strength static magnetic field (0.4 tesla). Ten healthy volunteers participated in this study. Using a 0.4 tesla magnetic resonance imaging (MRI) scanner and a quadrature head coil, three-dimensional T 1 -weighted images (3D-T 1 WIs) were obtained from each subject, twice on the same day. VBM8 software was used to construct segmented normalized images [gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) images]. The regions-of-interest (ROIs) of GM, WM, CSF, hippocampus (HC), orbital gyrus (OG), and cerebellum posterior lobe (CPL) were generated using WFU PickAtlas. The percentage change was defined as[100 × (measured volume with first segmented image - mean volume in each subject)/(mean volume in each subject)]The average percentage change was calculated as the percentage change in the 6 ROIs of the 10 subjects. The mean of the average percentage changes for each ROI was as follows: GM, 0.556%; WM, 0.324%; CSF, 0.573%; HC, 0.645%; OG, 1.74%; and CPL, 0.471%. The average percentage change was higher for the orbital gyrus than for the other ROIs. We consider that repeatability of the atlas-based method is similar between 0.4 and 1.5 tesla MR scanners. To our knowledge, this is the first report to show that the level of repeatability with a 0.4 tesla MR scanner is adequate for the estimation of brain volume change by the atlas-based method.

Dr. Jacob Cohen presents the H. Julian Allen award to Anthony Colaprete.

NASA Image and Video Library

2017-03-16

Dr. Jacob Cohen Director Office of Chief Scientist with Dr. Anthony Colaprete recipient of the H. Julian Allen Award In recognition as co-author of the outstanding scientific paper entitled "Detection of Water in the LCROSS Ejecta Pluma." Shown here Dr. Jacob Cohen presents the H. Julian Allen award to Anthony Colaprete.

Two-stage atlas subset selection in multi-atlas based image segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu

2015-06-15

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stagemore » atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The

Two-stage atlas subset selection in multi-atlas based image segmentation.

PubMed

Zhao, Tingting; Ruan, Dan

2015-06-01

Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas

Efficient Multi-Atlas Registration using an Intermediate Template Image

PubMed Central

Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

2017-01-01

Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3–4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects. PMID:28943702

Efficient multi-atlas registration using an intermediate template image

NASA Astrophysics Data System (ADS)

Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

2017-03-01

Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3-4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects.

Transcripts with in silico predicted RNA structure are enriched everywhere in the mouse brain

PubMed Central

2012-01-01

Background Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts. Results By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3’ UTR structures and correlated expression patterns. Conclusions Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function. PMID:22651826

Anatomical guidance for functional near-infrared spectroscopy: AtlasViewer tutorial

PubMed Central

Aasted, Christopher M.; Yücel, Meryem A.; Cooper, Robert J.; Dubb, Jay; Tsuzuki, Daisuke; Becerra, Lino; Petkov, Mike P.; Borsook, David; Dan, Ippeita; Boas, David A.

2015-01-01

Abstract. Functional near-infrared spectroscopy (fNIRS) is an optical imaging method that is used to noninvasively measure cerebral hemoglobin concentration changes induced by brain activation. Using structural guidance in fNIRS research enhances interpretation of results and facilitates making comparisons between studies. AtlasViewer is an open-source software package we have developed that incorporates multiple spatial registration tools to enable structural guidance in the interpretation of fNIRS studies. We introduce the reader to the layout of the AtlasViewer graphical user interface, the folder structure, and user files required in the creation of fNIRS probes containing sources and detectors registered to desired locations on the head, evaluating probe fabrication error and intersubject probe placement variability, and different procedures for estimating measurement sensitivity to different brain regions as well as image reconstruction performance. Further, we detail how AtlasViewer provides a generic head atlas for guiding interpretation of fNIRS results, but also permits users to provide subject-specific head anatomies to interpret their results. We anticipate that AtlasViewer will be a valuable tool in improving the anatomical interpretation of fNIRS studies. PMID:26157991

Allen figure and broken wheel visual acuity measurement in preschool children.

PubMed

Schmidt, P P

1992-02-01

In a masked investigation, 34 preschool children (n = 34, 19 females and 15 males) between the ages of 3 and 5 years (mean age = 4.1 years) enrolled in Project Headstart had their monocular and binocular visual acuity measured using the Broken Wheel and Allen figure methods. The results showed that 1) a greater range in acuity values was found with the Allen figure than Broken Wheel test, despite the identical Snellen equivalent acuity levels and similar probability of guessing criteria used for both Broken Wheel and Allen figure acuity measurement e.g., no strong statistical correlation (rOD = +0.22, rOS = -0.11 and rOU = +0.04; rho OD = +0.22, rho OS = -0.11, rho OU = 0.00) for the two tests was found; and 2) the Broken Wheel test appeared to discriminate between 20/30 and 20/40 acuity performance more consistently than did Allen figure and in a way not attributable to chance (p less than or equal to 0.003). In a separate evaluation, the Broken Wheel test showed consistency in the acuity measured. Broken Wheel acuity measurement, even with an average variation of +/- 5.6 percent from the corresponding Snellen standard, appears to be a valuable clinical tool to measure acuity in young children.

Rejuvenating Allen's Arc with the Geometric Mean.

ERIC Educational Resources Information Center

Phillips, William A.

1994-01-01

Contends that, despite ongoing criticism, Allen's arc elasticity formula remains entrenched in the microeconomics principles curriculum. Reviews the evolution and continuing scrutiny of the formula. Argues that the use of the geometric mean offers pedagogical advantages over the traditional arithmetic mean approach. (CFR)

Large-Scale Mass Spectrometry Imaging Investigation of Consequences of Cortical Spreading Depression in a Transgenic Mouse Model of Migraine

NASA Astrophysics Data System (ADS)

Carreira, Ricardo J.; Shyti, Reinald; Balluff, Benjamin; Abdelmoula, Walid M.; van Heiningen, Sandra H.; van Zeijl, Rene J.; Dijkstra, Jouke; Ferrari, Michel D.; Tolner, Else A.; McDonnell, Liam A.; van den Maagdenberg, Arn M. J. M.

2015-06-01

Cortical spreading depression (CSD) is the electrophysiological correlate of migraine aura. Transgenic mice carrying the R192Q missense mutation in the Cacna1a gene, which in patients causes familial hemiplegic migraine type 1 (FHM1), exhibit increased propensity to CSD. Herein, mass spectrometry imaging (MSI) was applied for the first time to an animal cohort of transgenic and wild type mice to study the biomolecular changes following CSD in the brain. Ninety-six coronal brain sections from 32 mice were analyzed by MALDI-MSI. All MSI datasets were registered to the Allen Brain Atlas reference atlas of the mouse brain so that the molecular signatures of distinct brain regions could be compared. A number of metabolites and peptides showed substantial changes in the brain associated with CSD. Among those, different mass spectral features showed significant ( t-test, P < 0.05) changes in the cortex, 146 and 377 Da, and in the thalamus, 1820 and 1834 Da, of the CSD-affected hemisphere of FHM1 R192Q mice. Our findings reveal CSD- and genotype-specific molecular changes in the brain of FHM1 transgenic mice that may further our understanding about the role of CSD in migraine pathophysiology. The results also demonstrate the utility of aligning MSI datasets to a common reference atlas for large-scale MSI investigations.

Palladium-Catalyzed SN2'-Cyclization of Ambivalent (Bromoalkadienyl)malonates: Preparation of Medium- to Large-Membered Endocyclic Allenes.

PubMed

Ichio, Hiroaki; Murakami, Hidetoshi; Chen, Yen-Chou; Takahashi, Tamotsu; Ogasawara, Masamichi

2017-07-21

A palladium-catalyzed reaction for preparing various endocyclic allenes was developed. The substrates for the reaction were readily available ω-(pronucleophile-tethered)-3-bromo-1,3-alkadienes, and a palladium-catalyst facilitated their unimolecular S N 2'-cyclization in the presence of potassium tert-butoxide to give the corresponding 9- to 16-membered endocyclic allenes in fair yields of up to 67% together with the dimeric 16- to 32-membered endocyclic bis-allenes and other oligomeric/polymeric intermolecular reaction products. For higher yields of the monomeric endocyclic allenes, the reaction needed to be conducted under high-dilution conditions. Using a chiral palladium catalyst, axially chiral endocyclic allenes were obtained in up to 70% ee.

Van Allen Probes Science Gateway: A Centralized Data Access Point

NASA Astrophysics Data System (ADS)

Romeo, G.; Barnes, R. J.; Ukhorskiy, A. Y.; Sotirelis, T.; Stephens, G. K.; Kessel, R.; Potter, M.

2015-12-01

The Van Allen Probes Science Gateway acts a centralized interface to the instrument Science Operation Centers (SOCs), provides mission planning tools, and hosts a number of science related activities such as the mission bibliography. Most importantly, the Gateway acts as the primary site for processing and delivering the Van Allen Probes Space Weather data to users. Over the past years, the web-site has been completely redesigned with the focus on easier navigation and improvements of the existing tools such as the orbit plotter, position calculator and magnetic footprint tool. In addition, a new data plotting facility has been added. Based on HTML5, which allows users to interactively plot Van Allen Probes science and space weather data. The user can tailor the tool to display exactly the plot they wish to see and then share this with other users via either a URL or by QR code. Various types of plots can be created, including, simple time series, data plotted as a function of orbital location, and time versus L-Shell, capability of visualizing data from both probes (A & B) on the same plot. In cooperation with all Van Allen Probes Instrument SOCs, the Science Gateway will soon be able to serve higher level data products (Level 3), and to visualize them via the above mentioned HTML5 interface. Users will also be able to create customized CDF files on the fly.

Segmentation of Image Ensembles via Latent Atlases

PubMed Central

Van Leemput, Koen; Menze, Bjoern H.; Wells, William M.; Golland, Polina

2010-01-01

Spatial priors, such as probabilistic atlases, play an important role in MRI segmentation. However, the availability of comprehensive, reliable and suitable manual segmentations for atlas construction is limited. We therefore propose a method for joint segmentation of corresponding regions of interest in a collection of aligned images that does not require labeled training data. Instead, a latent atlas, initialized by at most a single manual segmentation, is inferred from the evolving segmentations of the ensemble. The algorithm is based on probabilistic principles but is solved using partial differential equations (PDEs) and energy minimization criteria. We evaluate the method on two datasets, segmenting subcortical and cortical structures in a multi-subject study and extracting brain tumors in a single-subject multi-modal longitudinal experiment. We compare the segmentation results to manual segmentations, when those exist, and to the results of a state-of-the-art atlas-based segmentation method. The quality of the results supports the latent atlas as a promising alternative when existing atlases are not compatible with the images to be segmented. PMID:20580305

Transportation Improvement Program - FY 1997-2000 - Allen County

DOT National Transportation Integrated Search

1996-02-01

The Lima-Allen County Regional Planning Commission (LACRPC), as the Metropolitan Planning Organization (MPO) of the Lima Urbanized Area, in conjunction with the Ohio Department of Transportation (ODOT), is responsible for coordinating transportation ...

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation

PubMed Central

Li, Hai; Fan, Lingzhong; Zhuo, Junjie; Wang, Jiaojian; Zhang, Yu; Yang, Zhengyi; Jiang, Tianzi

2017-01-01

There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation. PMID:28611620

Atlas based brain volumetry: How to distinguish regional volume changes due to biological or physiological effects from inherent noise of the methodology.

PubMed

Opfer, Roland; Suppa, Per; Kepp, Timo; Spies, Lothar; Schippling, Sven; Huppertz, Hans-Jürgen

2016-05-01

Fully-automated regional brain volumetry based on structural magnetic resonance imaging (MRI) plays an important role in quantitative neuroimaging. In clinical trials as well as in clinical routine multiple MRIs of individual patients at different time points need to be assessed longitudinally. Measures of inter- and intrascanner variability are crucial to understand the intrinsic variability of the method and to distinguish volume changes due to biological or physiological effects from inherent noise of the methodology. To measure regional brain volumes an atlas based volumetry (ABV) approach was deployed using a highly elastic registration framework and an anatomical atlas in a well-defined template space. We assessed inter- and intrascanner variability of the method in 51 cognitively normal subjects and 27 Alzheimer dementia (AD) patients from the Alzheimer's Disease Neuroimaging Initiative by studying volumetric results of repeated scans for 17 compartments and brain regions. Median percentage volume differences of scan-rescans from the same scanner ranged from 0.24% (whole brain parenchyma in healthy subjects) to 1.73% (occipital lobe white matter in AD), with generally higher differences in AD patients as compared to normal subjects (e.g., 1.01% vs. 0.78% for the hippocampus). Minimum percentage volume differences detectable with an error probability of 5% were in the one-digit percentage range for almost all structures investigated, with most of them being below 5%. Intrascanner variability was independent of magnetic field strength. The median interscanner variability was up to ten times higher than the intrascanner variability. Copyright © 2016 Elsevier Inc. All rights reserved.

Low-rank Atlas Image Analyses in the Presence of Pathologies

PubMed Central

Liu, Xiaoxiao; Niethammer, Marc; Kwitt, Roland; Singh, Nikhil; McCormick, Matt; Aylward, Stephen

2015-01-01

We present a common framework, for registering images to an atlas and for forming an unbiased atlas, that tolerates the presence of pathologies such as tumors and traumatic brain injury lesions. This common framework is particularly useful when a sufficient number of protocol-matched scans from healthy subjects cannot be easily acquired for atlas formation and when the pathologies in a patient cause large appearance changes. Our framework combines a low-rank-plus-sparse image decomposition technique with an iterative, diffeomorphic, group-wise image registration method. At each iteration of image registration, the decomposition technique estimates a “healthy” version of each image as its low-rank component and estimates the pathologies in each image as its sparse component. The healthy version of each image is used for the next iteration of image registration. The low-rank and sparse estimates are refined as the image registrations iteratively improve. When that framework is applied to image-to-atlas registration, the low-rank image is registered to a pre-defined atlas, to establish correspondence that is independent of the pathologies in the sparse component of each image. Ultimately, image-to-atlas registrations can be used to define spatial priors for tissue segmentation and to map information across subjects. When that framework is applied to unbiased atlas formation, at each iteration, the average of the low-rank images from the patients is used as the atlas image for the next iteration, until convergence. Since each iteration’s atlas is comprised of low-rank components, it provides a population-consistent, pathology-free appearance. Evaluations of the proposed methodology are presented using synthetic data as well as simulated and clinical tumor MRI images from the brain tumor segmentation (BRATS) challenge from MICCAI 2012. PMID:26111390

Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network.

PubMed

Bludau, Sebastian; Mühleisen, Thomas W; Eickhoff, Simon B; Hawrylycz, Michael J; Cichon, Sven; Amunts, Katrin

2018-06-01

Decoding the chain from genes to cognition requires detailed insights how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas contains regional gene expression data, while the JuBrain Atlas offers three-dimensional cytoarchitectonic maps reflecting interindividual variability. To date, an integrated framework that combines the analytical benefits of both scientific platforms towards a multi-level brain atlas of adult humans was not available. We have, therefore, developed JuGEx, a new method for integrating tissue transcriptome and cytoarchitectonic segregation. We investigated differential gene expression in two JuBrain areas of the frontal pole that we have structurally and functionally characterized in previous studies. Our results show a significant upregulation of MAOA and TAC1 in the medial area frontopolaris which is a node in the limbic-cortical network and known to be susceptible for gray matter loss and behavioral dysfunction in patients with depression. The MAOA gene encodes an enzyme which is involved in the catabolism of dopamine, norepinephrine, serotonin, and other monoaminergic neurotransmitters. The TAC1 locus generates hormones that play a role in neuron excitations and behavioral responses. Overall, JuGEx provides a new tool for the scientific community that empowers research from basic, cognitive and clinical neuroscience in brain regions and disease models with regard to gene expression.

Pd-Catalyzed Asymmetric β-Hydride Elimination En Route to Chiral Allenes

PubMed Central

Crouch, Ian T.; Neff, Robynne K.; Frantz, Doug E.

2013-01-01

We wish to report our preliminary results on the discovery and development of a catalytic, asymmetric β-hydride elimination from vinyl Pd(II)-complexes derived from enol triflates to access chiral allenes. To achieve this, we developed a class of chiral phosphite ligands that demonstrate high enantioselectivity, allow access of either allene enantiomer, and are readily synthesized. The methodology is demonstrated on over 20 substrates and application to the formal asymmetric total synthesis of the natural product, (+)-epibatidine, is also provided. PMID:23488914

New experimental results in atlas-based brain morphometry

NASA Astrophysics Data System (ADS)

Gee, James C.; Fabella, Brian A.; Fernandes, Siddharth E.; Turetsky, Bruce I.; Gur, Ruben C.; Gur, Raquel E.

1999-05-01

In a previous meeting, we described a computational approach to MRI morphometry, in which a spatial warp mapping a reference or atlas image into anatomic alignment with the subject is first inferred. Shape differences with respect to the atlas are then studied by calculating the pointwise Jacobian determinant for the warp, which provides a measure of the change in differential volume about a point in the reference as it transforms to its corresponding position in the subject. In this paper, the method is used to analyze sex differences in the shape and size of the corpus callosum in an ongoing study of a large population of normal controls. The preliminary results of the current analysis support findings in the literature that have observed the splenium to be larger in females than in males.

STS-46 Pilot Allen uses cycle ergometer on OV-104's middeck

NASA Image and Video Library

1992-08-08

STS046-24-025 (31 July-8 Aug. 1992) --- Astronaut Andrew M. Allen, STS-46 pilot, exercises on the bicycle ergometer device on the flight deck of the Space Shuttle Atlantis as it makes one of its 127 total orbits for the eight-day mission. Allen, equipped with sensors for monitoring his biological systems during the run, was joined by four other NASA astronauts and two European scientists on the mission.

Bridging Neuroanatomy, Neuroradiology and Neurology: Three-Dimensional Interactive Atlas of Neurological Disorders

PubMed Central

Nowinski, W.L.; Chua, B.C.

2013-01-01

Understanding brain pathology along with the underlying neuroanatomy and the resulting neurological deficits is of vital importance in medical education and clinical practice. To facilitate and expedite this understanding, we created a three-dimensional (3D) interactive atlas of neurological disorders providing the correspondence between a brain lesion and the resulting disorder(s). The atlas contains a 3D highly parcellated atlas of normal neuroanatomy along with a brain pathology database. Normal neuroanatomy is divided into about 2,300 components, including the cerebrum, cerebellum, brainstem, spinal cord, arteries, veins, dural sinuses, tracts, cranial nerves (CN), white matter, deep gray nuclei, ventricles, visual system, muscles, glands and cervical vertebrae (C1-C5). The brain pathology database contains 144 focal and distributed synthesized lesions (70 vascular, 36 CN-related, and 38 regional anatomy-related), each lesion labeled with the resulting disorder and associated signs, symptoms, and/or syndromes compiled from materials reported in the literature. The initial view of each lesion was preset in terms of its location and size, surrounding surface and sectional (magnetic resonance) neuroanatomy, and labeling of lesion and neuroanatomy. In addition, a glossary of neurological disorders was compiled and for each disorder materials from textbooks were included to provide neurological description. This atlas of neurological disorders is potentially useful to a wide variety of users ranging from medical students, residents and nurses to general practitioners, neuroanatomists, neuroradiologists and neurologists, as it contains both normal (surface and sectional) brain anatomy and pathology correlated with neurological disorders presented in a visual and interactive way. PMID:23859280

Bridging neuroanatomy, neuroradiology and neurology: three-dimensional interactive atlas of neurological disorders.

PubMed

Nowinski, W L; Chua, B C

2013-06-01

Understanding brain pathology along with the underlying neuroanatomy and the resulting neurological deficits is of vital importance in medical education and clinical practice. To facilitate and expedite this understanding, we created a three-dimensional (3D) interactive atlas of neurological disorders providing the correspondence between a brain lesion and the resulting disorder(s). The atlas contains a 3D highly parcellated atlas of normal neuroanatomy along with a brain pathology database. Normal neuroanatomy is divided into about 2,300 components, including the cerebrum, cerebellum, brainstem, spinal cord, arteries, veins, dural sinuses, tracts, cranial nerves (CN), white matter, deep gray nuclei, ventricles, visual system, muscles, glands and cervical vertebrae (C1-C5). The brain pathology database contains 144 focal and distributed synthesized lesions (70 vascular, 36 CN-related, and 38 regional anatomy-related), each lesion labeled with the resulting disorder and associated signs, symptoms, and/or syndromes compiled from materials reported in the literature. The initial view of each lesion was preset in terms of its location and size, surrounding surface and sectional (magnetic resonance) neuroanatomy, and labeling of lesion and neuroanatomy. In addition, a glossary of neurological disorders was compiled and for each disorder materials from textbooks were included to provide neurological description. This atlas of neurological disorders is potentially useful to a wide variety of users ranging from medical students, residents and nurses to general practitioners, neuroanatomists, neuroradiologists and neurologists, as it contains both normal (surface and sectional) brain anatomy and pathology correlated with neurological disorders presented in a visual and interactive way.

A three-dimensional digital atlas of the dura mater based on human head MRI.

PubMed

Yang, Zhirong; Guo, Zhilin

2015-03-30

The goal of this paper was to design a three-dimensional (3D) digital dural atlas of the human brain for assisting neurosurgeons during the planning of an operation, medical research and teaching activities in neurosurgical anatomy. The 176 sagittal head magnetic resonance(MR) images of a 54-year-old female who suffered from the left posterior fossa tumor were processed and outlined, based on which a 3D dural model was created using the softwares of 3ds-max and Mimics. Then the model and images/anatomy photos were matched using the softwares of Z-brush and Photoshop to form the 3-D dural atlas. Dural anatomic photographs were needed to produce the 3D atlas in dural vault and skull base areas. The 3D dural atlas of the brain and related structures was successfully constructed using 73 dural delineations, the contours of dural model match very well on the dural structures of the original images in three orthogonal (axial, coronal and sagittal view) MR cross-sections. The atlas can be arbitrarily rotated and viewed from any direction. It can also be zoomed in and out directly using the zoom function. We successfully generated a 3D dural atlas of human brain, which can be used for repeated observation and research without limitations of time and shortage of corpses. In addition, the atlas has many potential applications in operative planning, surgical training, teaching activities, and so on. Copyright © 2014 Elsevier B.V. All rights reserved.

Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain

PubMed Central

Krienen, Fenna M.; Yeo, B. T. Thomas; Ge, Tian; Buckner, Randy L.; Sherwood, Chet C.

2016-01-01

The human brain is patterned with disproportionately large, distributed cerebral networks that connect multiple association zones in the frontal, temporal, and parietal lobes. The expansion of the cortical surface, along with the emergence of long-range connectivity networks, may be reflected in changes to the underlying molecular architecture. Using the Allen Institute’s human brain transcriptional atlas, we demonstrate that genes particularly enriched in supragranular layers of the human cerebral cortex relative to mouse distinguish major cortical classes. The topography of transcriptional expression reflects large-scale brain network organization consistent with estimates from functional connectivity MRI and anatomical tracing in nonhuman primates. Microarray expression data for genes preferentially expressed in human upper layers (II/III), but enriched only in lower layers (V/VI) of mouse, were cross-correlated to identify molecular profiles across the cerebral cortex of postmortem human brains (n = 6). Unimodal sensory and motor zones have similar molecular profiles, despite being distributed across the cortical mantle. Sensory/motor profiles were anticorrelated with paralimbic and certain distributed association network profiles. Tests of alternative gene sets did not consistently distinguish sensory and motor regions from paralimbic and association regions: (i) genes enriched in supragranular layers in both humans and mice, (ii) genes cortically enriched in humans relative to nonhuman primates, (iii) genes related to connectivity in rodents, (iv) genes associated with human and mouse connectivity, and (v) 1,454 gene sets curated from known gene ontologies. Molecular innovations of upper cortical layers may be an important component in the evolution of long-range corticocortical projections. PMID:26739559

Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain.

PubMed

Krienen, Fenna M; Yeo, B T Thomas; Ge, Tian; Buckner, Randy L; Sherwood, Chet C

2016-01-26

The human brain is patterned with disproportionately large, distributed cerebral networks that connect multiple association zones in the frontal, temporal, and parietal lobes. The expansion of the cortical surface, along with the emergence of long-range connectivity networks, may be reflected in changes to the underlying molecular architecture. Using the Allen Institute's human brain transcriptional atlas, we demonstrate that genes particularly enriched in supragranular layers of the human cerebral cortex relative to mouse distinguish major cortical classes. The topography of transcriptional expression reflects large-scale brain network organization consistent with estimates from functional connectivity MRI and anatomical tracing in nonhuman primates. Microarray expression data for genes preferentially expressed in human upper layers (II/III), but enriched only in lower layers (V/VI) of mouse, were cross-correlated to identify molecular profiles across the cerebral cortex of postmortem human brains (n = 6). Unimodal sensory and motor zones have similar molecular profiles, despite being distributed across the cortical mantle. Sensory/motor profiles were anticorrelated with paralimbic and certain distributed association network profiles. Tests of alternative gene sets did not consistently distinguish sensory and motor regions from paralimbic and association regions: (i) genes enriched in supragranular layers in both humans and mice, (ii) genes cortically enriched in humans relative to nonhuman primates, (iii) genes related to connectivity in rodents, (iv) genes associated with human and mouse connectivity, and (v) 1,454 gene sets curated from known gene ontologies. Molecular innovations of upper cortical layers may be an important component in the evolution of long-range corticocortical projections.

Atlas selection for hippocampus segmentation: Relevance evaluation of three meta-information parameters.

PubMed

Dill, Vanderson; Klein, Pedro Costa; Franco, Alexandre Rosa; Pinho, Márcio Sarroglia

2018-04-01

Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used. However, registration to many templates leads to a high computational cost. Researchers have proposed to use an atlas pre-selection technique based on meta-information followed by the selection of an atlas based on image similarity. Unfortunately, this method also presents a high computational cost due to the image-similarity process. Thus, it is desirable to pre-select a smaller number of atlases as long as this does not impact on the segmentation quality. To pick out an atlas that provides the best registration, we evaluate the use of three meta-information parameters (medical condition, age range, and gender) to choose the atlas. In this work, 24 atlases were defined and each is based on the combination of the three meta-information parameters. These atlases were used to segment 352 vol from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Hippocampus segmentation with each of these atlases was evaluated and compared to reference segmentations of the hippocampus, which are available from ADNI. The use of atlas selection by meta-information led to a significant gain in the Dice similarity coefficient, which reached 0.68 ± 0.11, compared to 0.62 ± 0.12 when using only the standard MNI152 atlas. Statistical analysis showed that the three meta-information parameters provided a significant improvement in the segmentation accuracy. Copyright © 2018 Elsevier Ltd

Evaluation of Atlas-Based White Matter Segmentation with Eve.

PubMed

Plassard, Andrew J; Hinton, Kendra E; Venkatraman, Vijay; Gonzalez, Christopher; Resnick, Susan M; Landman, Bennett A

2015-03-20

Multi-atlas labeling has come in wide spread use for whole brain labeling on magnetic resonance imaging. Recent challenges have shown that leading techniques are near (or at) human expert reproducibility for cortical gray matter labels. However, these approaches tend to treat white matter as essentially homogeneous (as white matter exhibits isointense signal on structural MRI). The state-of-the-art for white matter atlas is the single-subject Johns Hopkins Eve atlas. Numerous approaches have attempted to use tractography and/or orientation information to identify homologous white matter structures across subjects. Despite success with large tracts, these approaches have been plagued by difficulties in with subtle differences in course, low signal to noise, and complex structural relationships for smaller tracts. Here, we investigate use of atlas-based labeling to propagate the Eve atlas to unlabeled datasets. We evaluate single atlas labeling and multi-atlas labeling using synthetic atlases derived from the single manually labeled atlas. On 5 representative tracts for 10 subjects, we demonstrate that (1) single atlas labeling generally provides segmentations within 2mm mean surface distance, (2) morphologically constraining DTI labels within structural MRI white matter reduces variability, and (3) multi-atlas labeling did not improve accuracy. These efforts present a preliminary indication that single atlas labels with correction is reasonable, but caution should be applied. To purse multi-atlas labeling and more fully characterize overall performance, more labeled datasets would be necessary.

Enantioselective Synthesis of 5,7-Bicyclic Ring Systems from Axially Chiral Allenes Using a Rh(I)-Catalyzed Cyclocarbonylation Reaction

PubMed Central

Grillet, Francois; Brummond, Kay M.

2013-01-01

A transfer of chirality in an intramolecular Rh(I)-catalyzed allenic Pauson-Khand reaction (APKR) to access tetrahydroazulenones, tetrahydrocyclopenta[c]azepinones and dihydrocyclopenta[c]oxepinones enantioselectively (22 – 99% ee) is described. The substitution pattern of the allene affected the transfer of chiral information. Complete transfer of chirality was obtained for all trisubstituted allenes, but loss of chiral information was observed for disubstituted allenes. This work constitutes the first demonstration of a transfer of chiral information from an allene to the 5-position of a cyclopentenone using a cyclocarbonylation reaction. The absolute configuration of the corresponding cyclocarbonylation product was also established, something that is rarely done. PMID:23485149

Van Allen Probes Science Gateway and Space Weather Data Processing

NASA Astrophysics Data System (ADS)

Romeo, G.; Barnes, R. J.; Weiss, M.; Fox, N. J.; Mauk, B.; Potter, M.; Kessel, R.

2014-12-01

The Van Allen Probes Science Gateway acts as a centralized interface to the instrument Science Operation Centers (SOCs), provides mission planning tools, and hosts a number of science related activities such as the mission bibliography. Most importantly, the Gateway acts as the primary site for processing and delivering the VAP Space Weather data to users. Over the past year, the web-site has been completely redesigned with the focus on easier navigation and improvements of the existing tools such as the orbit plotter, position calculator and magnetic footprint tool. In addition, a new data plotting facility has been added. Based on HTML5, which allows users to interactively plot Van Allen Probes summary and space weather data. The user can tailor the tool to display exactly the plot they wish to see and then share this with other users via either a URL or by QR code. Various types of plots can be created, including simple time series, data plotted as a function of orbital location, and time versus L-Shell. We discuss the new Van Allen Probes Science Gateway and the Space Weather Data Pipeline.

Determining Core Plasmaspheric Electron Densities with the Van Allen Probes

NASA Astrophysics Data System (ADS)

De Pascuale, S.; Hartley, D.; Kurth, W. S.; Kletzing, C.; Thaller, S. A.; Wygant, J. R.

2016-12-01

We survey three methods for obtaining electron densities inside of the core plasmasphere region (L < 4) to the perigee of the Van Allen Probes (L 1.1) from September 2012 to December 2014. Using the EMFISIS instrument on board the Van Allen Probes, electron densities are extracted from the upper hybrid resonance to an uncertainty of 10%. Some measurements are subject to larger errors given interpretational issues, especially at low densities (L > 4) resulting from geomagnetic activity. At high densities EMFISIS is restricted by an upper observable limit near 3000 cm-3. As this limit is encountered above perigee, we employ two additional methods validated against EMFISIS measurements to determine electron densities deep within the plasmasphere (L < 2). EMFISIS can extrapolate density estimates to lower L by calculating high densities, in good agreement with the upper hybrid technique when applicable, from plasma wave properties. Calibrated measurements, from the Van Allen Probes EFW potential instrument, also extend into this range. In comparison with the published EMFISIS database we provide a metric for the validity of core plasmaspheric density measurements obtained from these methods and an empirical density model for use in wave and particle simulations.

Simulated Van Allen Belts Generated by Plasma Thruster in Tank 5

NASA Image and Video Library

1966-09-21

The model of the Earth housed inside Vacuum Tank 5 contained a coil which produced a magnetic field simulating that of the Earth. It was bombarded with a stream of ionized particles simulating the solar wind which impinges on the Earth's magnetic field. The bands or belts of luminous plasma seen in this image were suggestive of the Van Allen belts found around the Earth. Scientists at Lewis probed the plasma around the model and studied scaling laws in an attempt to find an explanation for the actual formation of the Van Allen belt.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than

Atlas-Independent, Electrophysiological Mapping of the Optimal Locus of Subthalamic Deep Brain Stimulation for the Motor Symptoms of Parkinson Disease.

PubMed

Conrad, Erin C; Mossner, James M; Chou, Kelvin L; Patil, Parag G

2018-05-23

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms of Parkinson disease (PD). However, motor outcomes can be variable, perhaps due to inconsistent positioning of the active contact relative to an unknown optimal locus of stimulation. Here, we determine the optimal locus of STN stimulation in a geometrically unconstrained, mathematically precise, and atlas-independent manner, using Unified Parkinson Disease Rating Scale (UPDRS) motor outcomes and an electrophysiological neuronal stimulation model. In 20 patients with PD, we mapped motor improvement to active electrode location, relative to the individual, directly MRI-visualized STN. Our analysis included a novel, unconstrained and computational electrical-field model of neuronal activation to estimate the optimal locus of DBS. We mapped the optimal locus to a tightly defined ovoid region 0.49 mm lateral, 0.88 mm posterior, and 2.63 mm dorsal to the anatomical midpoint of the STN. On average, this locus is 11.75 lateral, 1.84 mm posterior, and 1.08 mm ventral to the mid-commissural point. Our novel, atlas-independent method reveals a single, ovoid optimal locus of stimulation in STN DBS for PD. The methodology, here applied to UPDRS and PD, is generalizable to atlas-independent mapping of other motor and non-motor effects of DBS. © 2018 S. Karger AG, Basel.

Segmentation of brain structures in presence of a space-occupying lesion.

PubMed

Pollo, Claudio; Cuadra, Meritxell Bach; Cuisenaire, Olivier; Villemure, Jean-Guy; Thiran, Jean-Philippe

2005-02-15

Brain deformations induced by space-occupying lesions may result in unpredictable position and shape of functionally important brain structures. The aim of this study is to propose a method for segmentation of brain structures by deformation of a segmented brain atlas in presence of a space-occupying lesion. Our approach is based on an a priori model of lesion growth (MLG) that assumes radial expansion from a seeding point and involves three steps: first, an affine registration bringing the atlas and the patient into global correspondence; then, the seeding of a synthetic tumor into the brain atlas providing a template for the lesion; finally, the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. The method was applied on two meningiomas inducing a pure displacement of the underlying brain structures, and segmentation accuracy of ventricles and basal ganglia was assessed. Results show that the segmented structures were consistent with the patient's anatomy and that the deformation accuracy of surrounding brain structures was highly dependent on the accurate placement of the tumor seeding point. Further improvements of the method will optimize the segmentation accuracy. Visualization of brain structures provides useful information for therapeutic consideration of space-occupying lesions, including surgical, radiosurgical, and radiotherapeutic planning, in order to increase treatment efficiency and prevent neurological damage.

An anatomic transcriptional atlas of human glioblastoma.

PubMed

Puchalski, Ralph B; Shah, Nameeta; Miller, Jeremy; Dalley, Rachel; Nomura, Steve R; Yoon, Jae-Guen; Smith, Kimberly A; Lankerovich, Michael; Bertagnolli, Darren; Bickley, Kris; Boe, Andrew F; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Chapin, Mike; Datta, Suvro; Dee, Nick; Desta, Tsega; Dolbeare, Tim; Dotson, Nadezhda; Ebbert, Amanda; Feng, David; Feng, Xu; Fisher, Michael; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W; Gu, Guangyu; Hejazinia, Nika; Hohmann, John; Hothi, Parvinder; Howard, Robert; Joines, Kevin; Kriedberg, Ali; Kuan, Leonard; Lau, Chris; Lee, Felix; Lee, Hwahyung; Lemon, Tracy; Long, Fuhui; Mastan, Naveed; Mott, Erika; Murthy, Chantal; Ngo, Kiet; Olson, Eric; Reding, Melissa; Riley, Zack; Rosen, David; Sandman, David; Shapovalova, Nadiya; Slaughterbeck, Clifford R; Sodt, Andrew; Stockdale, Graham; Szafer, Aaron; Wakeman, Wayne; Wohnoutka, Paul E; White, Steven J; Marsh, Don; Rostomily, Robert C; Ng, Lydia; Dang, Chinh; Jones, Allan; Keogh, Bart; Gittleman, Haley R; Barnholtz-Sloan, Jill S; Cimino, Patrick J; Uppin, Megha S; Keene, C Dirk; Farrokhi, Farrokh R; Lathia, Justin D; Berens, Michael E; Iavarone, Antonio; Bernard, Amy; Lein, Ed; Phillips, John W; Rostad, Steven W; Cobbs, Charles; Hawrylycz, Michael J; Foltz, Greg D

2018-05-11

Glioblastoma is an aggressive brain tumor that carries a poor prognosis. The tumor's molecular and cellular landscapes are complex, and their relationships to histologic features routinely used for diagnosis are unclear. We present the Ivy Glioblastoma Atlas, an anatomically based transcriptional atlas of human glioblastoma that aligns individual histologic features with genomic alterations and gene expression patterns, thus assigning molecular information to the most important morphologic hallmarks of the tumor. The atlas and its clinical and genomic database are freely accessible online data resources that will serve as a valuable platform for future investigations of glioblastoma pathogenesis, diagnosis, and treatment. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

PREDICTING APHASIA TYPE FROM BRAIN DAMAGE MEASURED WITH STRUCTURAL MRI

PubMed Central

Yourganov, Grigori; Smith, Kimberly G.; Fridriksson, Julius; Rorden, Chris

2015-01-01

Chronic aphasia is a common consequence of a left-hemisphere stroke. Since the early insights by Broca and Wernicke, studying the relationship between the loci of cortical damage and patterns of language impairment has been one of the concerns of aphasiology. We utilized multivariate classification in a cross-validation framework to predict the type of chronic aphasia from the spatial pattern of brain damage. Our sample consisted of 98 patients with five types of aphasia (Broca’s, Wernicke’s, global, conduction, and anomic), classified based on scores on the Western Aphasia Battery. Binary lesion maps were obtained from structural MRI scans (obtained at least 6 months poststroke, and within 2 days of behavioural assessment); after spatial normalization, the lesions were parcellated into a disjoint set of brain areas. The proportion of damage to the brain areas was used to classify patients’ aphasia type. To create this parcellation, we relied on five brain atlases; our classifier (support vector machine) could differentiate between different kinds of aphasia using any of the five parcellations. In our sample, the best classification accuracy was obtained when using a novel parcellation that combined two previously published brain atlases, with the first atlas providing the segmentation of grey matter, and the second atlas used to segment the white matter. For each aphasia type, we computed the relative importance of different brain areas for distinguishing it from other aphasia types; our findings were consistent with previously published reports of lesion locations implicated in different types of aphasia. Overall, our results revealed that automated multivariate classification could distinguish between aphasia types based on damage to atlas-defined brain areas. PMID:26465238

Predicting aphasia type from brain damage measured with structural MRI.

PubMed

Yourganov, Grigori; Smith, Kimberly G; Fridriksson, Julius; Rorden, Chris

2015-12-01

Chronic aphasia is a common consequence of a left-hemisphere stroke. Since the early insights by Broca and Wernicke, studying the relationship between the loci of cortical damage and patterns of language impairment has been one of the concerns of aphasiology. We utilized multivariate classification in a cross-validation framework to predict the type of chronic aphasia from the spatial pattern of brain damage. Our sample consisted of 98 patients with five types of aphasia (Broca's, Wernicke's, global, conduction, and anomic), classified based on scores on the Western Aphasia Battery (WAB). Binary lesion maps were obtained from structural MRI scans (obtained at least 6 months poststroke, and within 2 days of behavioural assessment); after spatial normalization, the lesions were parcellated into a disjoint set of brain areas. The proportion of damage to the brain areas was used to classify patients' aphasia type. To create this parcellation, we relied on five brain atlases; our classifier (support vector machine - SVM) could differentiate between different kinds of aphasia using any of the five parcellations. In our sample, the best classification accuracy was obtained when using a novel parcellation that combined two previously published brain atlases, with the first atlas providing the segmentation of grey matter, and the second atlas used to segment the white matter. For each aphasia type, we computed the relative importance of different brain areas for distinguishing it from other aphasia types; our findings were consistent with previously published reports of lesion locations implicated in different types of aphasia. Overall, our results revealed that automated multivariate classification could distinguish between aphasia types based on damage to atlas-defined brain areas. Copyright © 2015 Elsevier Ltd. All rights reserved.

Automated Identification and Shape Analysis of Chorus Elements in the Van Allen Radiation Belts

NASA Astrophysics Data System (ADS)

Sen Gupta, Ananya; Kletzing, Craig; Howk, Robin; Kurth, William; Matheny, Morgan

2017-12-01

An important goal of the Van Allen Probes mission is to understand wave-particle interaction by chorus emissions in terrestrial Van Allen radiation belts. To test models, statistical characterization of chorus properties, such as amplitude variation and sweep rates, is an important scientific goal. The Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite provides measurements of wave electric and magnetic fields as well as DC magnetic fields for the Van Allen Probes mission. However, manual inspection across terabytes of EMFISIS data is not feasible and as such introduces human confirmation bias. We present signal processing techniques for automated identification, shape analysis, and sweep rate characterization of high-amplitude whistler-mode chorus elements in the Van Allen radiation belts. Specifically, we develop signal processing techniques based on the radon transform that disambiguate chorus elements with a dominant sweep rate against hiss-like chorus. We present representative results validating our techniques and also provide statistical characterization of detected chorus elements across a case study of a 6 s epoch.

A whole brain atlas with sub-parcellation of cortical gyri using resting fMRI

NASA Astrophysics Data System (ADS)

Joshi, Anand A.; Choi, Soyoung; Sonkar, Gaurav; Chong, Minqi; Gonzalez-Martinez, Jorge; Nair, Dileep; Shattuck, David W.; Damasio, Hanna; Leahy, Richard M.

2017-02-01

The new hybrid-BCI-DNI atlas is a high-resolution MPRAGE, single-subject atlas, constructed using both anatomical and functional information to guide the parcellation of the cerebral cortex. Anatomical labeling was performed manually on coronal single-slice images guided by sulcal and gyral landmarks to generate the original (non-hybrid) BCI-DNI atlas. Functional sub-parcellations of the gyral ROIs were then generated from 40 minimally preprocessed resting fMRI datasets from the HCP database. Gyral ROIs were transferred from the BCI-DNI atlas to the 40 subjects using the HCP grayordinate space as a reference. For each subject, each gyral ROI was subdivided using the fMRI data by applying spectral clustering to a similarity matrix computed from the fMRI time-series correlations between each vertex pair. The sub-parcellations were then transferred back to the original cortical mesh to create the subparcellated hBCI-DNI atlas with a total of 67 cortical regions per hemisphere. To assess the stability of the gyral subdivisons, a separate set of 60 HCP datasets were processed as follows: 1) coregistration of the structural scans to the hBCI-DNI atlas; 2) coregistration of the anatomical BCI-DNI atlas without functional subdivisions, followed by sub-parcellation of each subject's resting fMRI data as described above. We then computed consistency between the anatomically-driven delineation of each gyral subdivision and that obtained per subject using individual fMRI data. The gyral sub-parcellations generated by atlas-based registration show variable but generally good overlap of the confidence intervals with the resting fMRI-based subdivisions. These consistency measures will provide a quantitative measure of reliability of each subdivision to users of the atlas.

Test-retest assessment of cortical activation induced by repetitive transcranial magnetic stimulation with brain atlas-guided optical topography

NASA Astrophysics Data System (ADS)

Tian, Fenghua; Kozel, F. Andrew; Yennu, Amarnath; Croarkin, Paul E.; McClintock, Shawn M.; Mapes, Kimberly S.; Husain, Mustafa M.; Liu, Hanli

2012-11-01

Repetitive transcranial magnetic stimulation (rTMS) is a technology that stimulates neurons with rapidly changing magnetic pulses with demonstrated therapeutic applications for various neuropsychiatric disorders. Functional near-infrared spectroscopy (fNIRS) is a suitable tool to assess rTMS-evoked brain responses without interference from the magnetic or electric fields generated by the TMS coil. We have previously reported a channel-wise study of combined rTMS/fNIRS on the motor and prefrontal cortices, showing a robust decrease of oxygenated hemoglobin concentration (Δ[HbO2]) at the sites of 1-Hz rTMS and the contralateral brain regions. However, the reliability of this putative clinical tool is unknown. In this study, we develop a rapid optical topography approach to spatially characterize the rTMS-evoked hemodynamic responses on a standard brain atlas. A hemispherical approximation of the brain is employed to convert the three-dimensional topography on the complex brain surface to a two-dimensional topography in the spherical coordinate system. The test-retest reliability of the combined rTMS/fNIRS is assessed using repeated measurements performed two to three days apart. The results demonstrate that the Δ[HbO2] amplitudes have moderate-to-high reliability at the group level; and the spatial patterns of the topographic images have high reproducibility in size and a moderate degree of overlap at the individual level.

Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.

PubMed

Wang, J; Hao, Z; Wang, H

2018-01-01

The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC). The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

Simulation and assessment of cerebrovascular damage in deep brain stimulation using a stereotactic atlas of vasculature and structure derived from multiple 3- and 7-tesla scans.

PubMed

Nowinski, Wieslaw L; Chua, Beng Choon; Volkau, Ihar; Puspitasari, Fiftarina; Marchenko, Yevgen; Runge, Val M; Knopp, Michael V

2010-12-01

The most severe complication of deep brain stimulation (DBS) is intracranial hemorrhage. Detailed knowledge of the cerebrovasculature could reduce the rate of this disorder. Morphological scans typically acquired in stereotactic and functional neurosurgery (SFN) by using 1.5-T (or sometimes even 3-T) imaging units poorly depict the vasculature. Advanced angiographic imaging, including 3- and 7-T 3D time-of-flight and susceptibility weighted imaging as well as 320-slice CT angiography, depict the vessels in great detail. However, these acquisitions are not used in SFN clinical practice, and robust methods for their processing are not available yet. Therefore, the authors proposed the use of a detailed 3D stereotactic cerebrovascular atlas to assist in SFN planning and to potentially reduce DBS-induced hemorrhage. A very detailed 3D cerebrovascular atlas of arteries, veins, and dural sinuses was constructed from multiple 3- and 7-T scans. The atlas contained>900 vessels, each labeled with a name and diameter with the smallest having a 90-μm diameter. The cortical areas, ventricular system, and subcortical structures were fully segmented and labeled, including the main stereotactic target structures: subthalamic nucleus, ventral intermediate nucleus of the thalamus, and internal globus pallidus. The authors also developed a computer simulator with the embedded atlas that was able to compute the effective electrode trajectory by minimizing penetration of the cerebrovascular system and vital brain structures by a DBS electrode. The simulator provides the neurosurgeon with functions for atlas manipulation, target selection, trajectory planning and editing, 3D display and manipulation, and electrode-brain penetration calculation. This simulation demonstrated that a DBS electrode inserted in the middle frontal gyrus may intersect several arteries and veins including 1) the anteromedial frontal artery of the anterior cerebral artery as well as the prefrontal artery and the

76 FR 36318 - Safety Zone; Waterway Closure, Morgan City-Port Allen Route From Mile Marker 0 to Port Allen Lock

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-22

... to hazards associated with rising flood water. DATES: Effective Date: this rule is effective in the..., vessels and tows from the hazards associated with rising flood water on the Morgan City-Port Allen Route... system, vessels and tows from destruction, loss or injury due to the hazards associated with rising flood...

Gold(I)-Catalysed Hydroarylation of 1,3-Disubstituted Allenes with Efficient Axial-to-Point Chirality Transfer.

PubMed

Sutherland, Daniel R; Kinsman, Luke; Angiolini, Stuart M; Rosair, Georgina M; Lee, Ai-Lan

2018-05-11

Hydroarylation of enantioenriched 1,3-disubstituted allenes has the potential to proceed with axial-to-point chirality transfer to yield enantioenriched allylated (hetero)aryl compounds. However, the gold-catalysed intermolecular reaction was previously reported to occur with no chirality transfer owing to competing allene racemisation. Herein, we describe the development of the first intermolecular hydroarylations of allenes to proceed with efficient chirality transfer and summarise some of the key criteria for achieving high regio- and stereoselectivity. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Astronaut Joseph P. Allen, STS-5 crew member, in front of open hatch

NASA Technical Reports Server (NTRS)

1982-01-01

Astronaut Joseph P. Allen, right, STS-5 mission specialist, slips on jacket portion of his Shuttle constant-wear garment in the White room at Launch Pad 39A at the Kennedy Space Center (KSC). Astronaut William B. Lenoir, STS-5's other mission specialist, left, waits to enter the Columbia, whose open hatch is at center. Electrodes on Allen's face and head are for monitoring his reflexes during launch.

Clinical Evaluation of Zero-Echo-Time Attenuation Correction for Brain 18F-FDG PET/MRI: Comparison with Atlas Attenuation Correction.

PubMed

Sekine, Tetsuro; Ter Voert, Edwin E G W; Warnock, Geoffrey; Buck, Alfred; Huellner, Martin; Veit-Haibach, Patrick; Delso, Gaspar

2016-12-01

Accurate attenuation correction (AC) on PET/MR is still challenging. The purpose of this study was to evaluate the clinical feasibility of AC based on fast zero-echo-time (ZTE) MRI by comparing it with the default atlas-based AC on a clinical PET/MR scanner. We recruited 10 patients with malignant diseases not located on the brain. In all patients, a clinically indicated whole-body 18 F-FDG PET/CT scan was acquired. In addition, a head PET/MR scan was obtained voluntarily. For each patient, 2 AC maps were generated from the MR images. One was atlas-AC, derived from T1-weighted liver acquisition with volume acceleration flex images (clinical standard). The other was ZTE-AC, derived from proton-density-weighted ZTE images by applying tissue segmentation and assigning continuous attenuation values to the bone. The AC map generated by PET/CT was used as a silver standard. On the basis of each AC map, PET images were reconstructed from identical raw data on the PET/MR scanner. All PET images were normalized to the SPM5 PET template. After that, these images were qualified visually and quantified in 67 volumes of interest (VOIs; automated anatomic labeling, atlas). Relative differences and absolute relative differences between PET images based on each AC were calculated. 18 F-FDG uptake in all 670 VOIs and generalized merged VOIs were compared using a paired t test. Qualitative analysis shows that ZTE-AC was robust to patient variability. Nevertheless, misclassification of air and bone in mastoid and nasal areas led to the overestimation of PET in the temporal lobe and cerebellum (%diff of ZTE-AC, 2.46% ± 1.19% and 3.31% ± 1.70%, respectively). The |%diff| of all 670 VOIs on ZTE was improved by approximately 25% compared with atlas-AC (ZTE-AC vs. atlas-AC, 1.77% ± 1.41% vs. 2.44% ± 1.63%, P < 0.01). In 2 of 7 generalized VOIs, |%diff| on ZTE-AC was significantly smaller than atlas-AC (ZTE-AC vs. atlas-AC: insula and cingulate, 1.06% ± 0.67% vs. 2.22% ± 1.10%, P < 0

Replacement of two amino acids of 9R-dioxygenase-allene oxide synthase of Aspergillus niger inverts the chirality of the hydroperoxide and the allene oxide.

PubMed

Sooman, Linda; Wennman, Anneli; Hamberg, Mats; Hoffmann, Inga; Oliw, Ernst H

2016-02-01

The genome of Aspergillus niger codes for a fusion protein (EHA25900), which can be aligned with ~50% sequence identity to 9S-dioxygenase (DOX)-allene oxide synthase (AOS) of Fusarium oxysporum, homologues of the Fusarium and Colletotrichum complexes and with over 62% sequence identity to homologues of Aspergilli, including (DOX)-9R-AOS of Aspergillus terreus. The aims were to characterize the enzymatic activities of EHA25900 and to identify crucial amino acids for the stereospecificity. Recombinant EHA25900 oxidized 18:2n-6 sequentially to 9R-hydroperoxy-10(E),12(Z)-octadecadienoic acid (9R-HPODE) and to a 9R(10)-allene oxide. 9S- and 9R-DOX-AOS catalyze abstraction of the pro-R hydrogen at C-11, but the direction of oxygen insertion differs. A comparison between twelve 9-DOX domains of 9S- and 9R-DOX-AOS revealed conserved amino acid differences, which could contribute to the chirality of products. The Gly616Ile replacement of 9R-DOX-AOS (A. niger) increased the biosynthesis of 9S-HPODE and the 9S(10)-allene oxide, whereas the Phe627Leu replacement led to biosynthesis of 9S-HPODE and the 9S(10)-allene oxide as main products. The double mutant (Gly616Ile, Phe627Leu) formed over 90% of the 9S stereoisomer of HPODE. 9S-HPODE was formed by antarafacial hydrogen abstraction and oxygen insertion, i.e., the original H-abstraction was retained but the product chirality was altered. We conclude that 9R-DOX-AOS can be altered to 9S-DOX-AOS by replacement of two amino acids (Gly616Ile, Phe627Leu) in the DOX domain. Copyright © 2015 Elsevier B.V. All rights reserved.

Automatic control model of water filling system with Allen Bradley Micrologix 1400 PLC

NASA Astrophysics Data System (ADS)

Harahap, R.; Adyatma, AF; Fahmi, F.

2018-02-01

Programmable Logic Controller or PLC today plays an important role in most industrial control systems. PLC usage can be encountered in almost all fields of industry, not only in the manufacturing world but also on many other things such as elevators in office buildings, hotels hospitals, and others. PLC is an electronic control tool that operates in logic that its programming can be modified with relative ease. As with any controller in general, the PLC processes input signals to further discharge output according to the desired program. PLC usage is very broad because of its high reliability, can be reprogrammed or modified with relative ease, and very helpful in the tracking troubleshooting. One type of existing PLC is Allen Bradley PLC. Allen Bradley PLC program is commonly used in various industries. PLC Allen Bradley (AB) has several types, and one of them is the type of Micrologic 1400. In this study we design a system as a comparison with the conventional system. For that to explore the use of a PLC program which will be supported by a simulator tool, including a program to RSLogic 500, how to programming, monitoring via RSView32, and modification. It is expected to understand the application aspect of operation and programming of this specific PLC and its potential. The purpose of this research is to design water filling automation system by using Allen Bradley Micrologic 1400 type 1766-L32BXB PLC, empowering the use of Allen Bradley Micrologic 1400 PLC and to regulate the desired process to obtain efficiency and effectiveness compared with conventional system arrangement using Relay.

[The brain in stereotaxic coordinates (a textbook for colleges)].

PubMed

Budantsev, A Iu; Kisliuk, O S; Shul'govskiĭ, V V; Rykunov, D S; Iarkov, A V

1993-01-01

The present textbook is directed forward students of universities and medical colleges, young scientists and practicing doctors dealing with stereotaxic method. The Paxinos and Watson stereotaxic rat brain atlas (1982) is the basis of the textbook. The atlas has been transformed into computer educational program and seven laboratory works: insertion of the electrode into brain, microelectrophoresis, microinjection of drugs into brain, electrolytic destruction in the brain structures, local brain superfusion. The laboratory works are compiled so that they allow not only to study practical use of the stereotaxic method but to model simple problems involving stereotaxic surgery in the deep structures of brain. The textbook is intended for carrying by IBM PC/AT computers. The volume of the textbook is 1.7 Mbytes.

Robust Estimation of Electron Density From Anatomic Magnetic Resonance Imaging of the Brain Using a Unifying Multi-Atlas Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Shangjie; Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, California; Hara, Wendy

Purpose: To develop a reliable method to estimate electron density based on anatomic magnetic resonance imaging (MRI) of the brain. Methods and Materials: We proposed a unifying multi-atlas approach for electron density estimation based on standard T1- and T2-weighted MRI. First, a composite atlas was constructed through a voxelwise matching process using multiple atlases, with the goal of mitigating effects of inherent anatomic variations between patients. Next we computed for each voxel 2 kinds of conditional probabilities: (1) electron density given its image intensity on T1- and T2-weighted MR images; and (2) electron density given its spatial location in a referencemore » anatomy, obtained by deformable image registration. These were combined into a unifying posterior probability density function using the Bayesian formalism, which provided the optimal estimates for electron density. We evaluated the method on 10 patients using leave-one-patient-out cross-validation. Receiver operating characteristic analyses for detecting different tissue types were performed. Results: The proposed method significantly reduced the errors in electron density estimation, with a mean absolute Hounsfield unit error of 119, compared with 140 and 144 (P<.0001) using conventional T1-weighted intensity and geometry-based approaches, respectively. For detection of bony anatomy, the proposed method achieved an 89% area under the curve, 86% sensitivity, 88% specificity, and 90% accuracy, which improved upon intensity and geometry-based approaches (area under the curve: 79% and 80%, respectively). Conclusion: The proposed multi-atlas approach provides robust electron density estimation and bone detection based on anatomic MRI. If validated on a larger population, our work could enable the use of MRI as a primary modality for radiation treatment planning.« less

9. Historic American Buildings Survey Allen L. Hubbard, Photographer December ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

9. Historic American Buildings Survey Allen L. Hubbard, Photographer December 1, 1936 FIREPLACE (Southwest corner room 1st floor) - Fort Western, Main Building, Bowman Street, Augusta, Kennebec County, ME

4. Historic American Buildings Survey Allen L. Hubbard, Photographer December ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. Historic American Buildings Survey Allen L. Hubbard, Photographer December 1, 1936 FIREPLACE WALL (northwest room 1st floor) - Fort Western, Main Building, Bowman Street, Augusta, Kennebec County, ME

An extensive assessment of network alignment algorithms for comparison of brain connectomes.

PubMed

Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario

2017-06-06

Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.

Automated tissue classification of pediatric brains from magnetic resonance images using age-specific atlases

NASA Astrophysics Data System (ADS)

Metzger, Andrew; Benavides, Amanda; Nopoulos, Peg; Magnotta, Vincent

2016-03-01

The goal of this project was to develop two age appropriate atlases (neonatal and one year old) that account for the rapid growth and maturational changes that occur during early development. Tissue maps from this age group were initially created by manually correcting the resulting tissue maps after applying an expectation maximization (EM) algorithm and an adult atlas to pediatric subjects. The EM algorithm classified each voxel into one of ten possible tissue types including several subcortical structures. This was followed by a novel level set segmentation designed to improve differentiation between distal cortical gray matter and white matter. To minimize the req uired manual corrections, the adult atlas was registered to the pediatric scans using high -dimensional, symmetric image normalization (SyN) registration. The subject images were then mapped to an age specific atlas space, again using SyN registration, and the resulting transformation applied to the manually corrected tissue maps. The individual maps were averaged in the age specific atlas space and blurred to generate the age appropriate anatomical priors. The resulting anatomical priors were then used by the EM algorithm to re-segment the initial training set as well as an independent testing set. The results from the adult and age-specific anatomical priors were compared to the manually corrected results. The age appropriate atlas provided superior results as compared to the adult atlas. The image analysis pipeline used in this work was built using the open source software package BRAINSTools.

8. Historic American Buildings Survey Allen L. Hubbard, Photographer December ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. Historic American Buildings Survey Allen L. Hubbard, Photographer December 1, 1936 FIREPLACE (1st floor east central room) (kitchen) - Fort Western, Main Building, Bowman Street, Augusta, Kennebec County, ME

12. Historic American Buildings Survey Allen L. Hubbard, Photographer December ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

12. Historic American Buildings Survey Allen L. Hubbard, Photographer December 1, 1936 CHEST (North room 3rd floor) (SWISS FURNITURE) - Fort Western, Main Building, Bowman Street, Augusta, Kennebec County, ME

13. Historic American Buildings Survey Allen L. Hubbard, Photographer December ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

13. Historic American Buildings Survey Allen L. Hubbard, Photographer December 1, 1936 CHEST (North room 3rd floor) (SWISS FURNITURE) - Fort Western, Main Building, Bowman Street, Augusta, Kennebec County, ME

11. Historic American Buildings Survey Allen L. Hubbard, Photographer December ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

11. Historic American Buildings Survey Allen L. Hubbard, Photographer December 1, 1936 SOUTHWEST CORNER ROOM (2nd floor, east wall) - Fort Western, Main Building, Bowman Street, Augusta, Kennebec County, ME

10. Historic American Buildings Survey Allen L. Hubbard, Photographer December ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

10. Historic American Buildings Survey Allen L. Hubbard, Photographer December 1, 1936 (Northwest cor. room 2nd floor) East Wall - Fort Western, Main Building, Bowman Street, Augusta, Kennebec County, ME

Ligand-Controlled Regioselective Copper-Catalyzed Trifluoromethylation To Generate (Trifluoromethyl)allenes.

PubMed

Ambler, Brett R; Peddi, Santosh; Altman, Ryan A

2015-05-15

"Cu-CF3" species have been used historically for a broad spectrum of nucleophilic trifluoromethylation reactions. Although recent advancements have employed ligands to stabilize and harness the reactivity of this key organometallic intermediate, the ability of a ligand to differentiate a regiochemical outcome of a Cu-CF3-mediated or -catalyzed reaction has not been previously reported. Herein, we report the first example of a Cu-catalyzed trifluoromethylation reaction in which a ligand controls the regiochemical outcome. More specifically, we demonstrate the ability of bipyridyl-derived ligands to control the regioselectivity of the Cu-catalyzed nucleophilic trifluoromethylation reactions of propargyl electrophiles to generate (trifluoromethyl)allenes. This method provides a variety of di-, tri-, and tetrasubstituted (trifluoromethyl)allenes, which can be further modified to generate complex fluorinated substructures.

Multi-scale hippocampal parcellation improves atlas-based segmentation accuracy

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; McHugo, Maureen; Heckers, Stephan; Landman, Bennett A.

2017-02-01

Known for its distinct role in memory, the hippocampus is one of the most studied regions of the brain. Recent advances in magnetic resonance imaging have allowed for high-contrast, reproducible imaging of the hippocampus. Typically, a trained rater takes 45 minutes to manually trace the hippocampus and delineate the anterior from the posterior segment at millimeter resolution. As a result, there has been a significant desire for automated and robust segmentation of the hippocampus. In this work we use a population of 195 atlases based on T1-weighted MR images with the left and right hippocampus delineated into the head and body. We initialize the multi-atlas segmentation to a region directly around each lateralized hippocampus to both speed up and improve the accuracy of registration. This initialization allows for incorporation of nearly 200 atlases, an accomplishment which would typically involve hundreds of hours of computation per target image. The proposed segmentation results in a Dice similiarity coefficient over 0.9 for the full hippocampus. This result outperforms a multi-atlas segmentation using the BrainCOLOR atlases (Dice 0.85) and FreeSurfer (Dice 0.75). Furthermore, the head and body delineation resulted in a Dice coefficient over 0.87 for both structures. The head and body volume measurements also show high reproducibility on the Kirby 21 reproducibility population (R2 greater than 0.95, p < 0.05 for all structures). This work signifies the first result in an ongoing work to develop a robust tool for measurement of the hippocampus and other temporal lobe structures.

MRI-based treatment planning with pseudo CT generated through atlas registration.

PubMed

Uh, Jinsoo; Merchant, Thomas E; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-05-01

To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787-0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%-98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at

MRI-based treatment planning with pseudo CT generated through atlas registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uh, Jinsoo, E-mail: jinsoo.uh@stjude.org; Merchant, Thomas E.; Hua, Chiaho

2014-05-15

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration ofmore » conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and

MRI-based treatment planning with pseudo CT generated through atlas registration

PubMed Central

Uh, Jinsoo; Merchant, Thomas E.; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-01-01

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the

An Estimation of Turbulent Characteristics in the Low-Level Region of Intense Hurricanes Allen (1980) and Hugo (1989)

DTIC Science & Technology

2011-05-01

An Estimation of Turbulent Characteristics in the Low-Level Region of Intense Hurricanes Allen (1980) and Hugo (1989) JUN A. ZHANG Rosenstiel School...aircraft that penetrated the eyewalls of category 5 Hurricane Hugo (1989) and category 4 Hurricane Allen (1980) between 1 km and the sea surface...to 00-00-2010 4. TITLE AND SUBTITLE An Estimation of Turbulent Characteristics in the Low-Level Region of Intense Hurricanes Allen (1980) and Hugo

Probabilistic atlas and geometric variability estimation to drive tissue segmentation.

PubMed

Xu, Hao; Thirion, Bertrand; Allassonnière, Stéphanie

2014-09-10

Computerized anatomical atlases play an important role in medical image analysis. While an atlas usually refers to a standard or mean image also called template, which presumably represents well a given population, it is not enough to characterize the observed population in detail. A template image should be learned jointly with the geometric variability of the shapes represented in the observations. These two quantities will in the sequel form the atlas of the corresponding population. The geometric variability is modeled as deformations of the template image so that it fits the observations. In this paper, we provide a detailed analysis of a new generative statistical model based on dense deformable templates that represents several tissue types observed in medical images. Our atlas contains both an estimation of probability maps of each tissue (called class) and the deformation metric. We use a stochastic algorithm for the estimation of the probabilistic atlas given a dataset. This atlas is then used for atlas-based segmentation method to segment the new images. Experiments are shown on brain T1 MRI datasets. Copyright © 2014 John Wiley & Sons, Ltd.

Astronaut Andrew M. Allen, mission commander, sets up systems for a television downlink on the

NASA Technical Reports Server (NTRS)

1996-01-01

STS-75 ONBOARD VIEW --- Astronaut Andrew M. Allen, mission commander, sets up systems for a television downlink on the flight deck of the Space Shuttle Columbia. Allen was joined by four other astronauts and an international payload specialist for more than 16 days of research aboard Columbia. The photograph was taken with a 70mm handheld camera.

James Van Allen and His Namesake NASA Mission

NASA Astrophysics Data System (ADS)

Baker, D. N.; Hoxie, V. C.; Jaynes, A.; Kale, A.; Kanekal, S. G.; Li, X.; Reeves, G. D.; Spence, H. E.

2013-12-01

In many ways, James A. Van Allen defined and "invented" modern space research. His example showed the way for government-university partners to pursue basic research that also served important national and international goals. He was a tireless advocate for space exploration and for the role of space science in the spectrum of national priorities.

An atlas-based multimodal registration method for 2D images with discrepancy structures.

PubMed

Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng

2018-06-04

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.

Three-dimensional stereotactic atlas of the extracranial vasculature correlated with the intracranial vasculature, cranial nerves, skull and muscles

PubMed Central

Shoon Let Thaung, Thant; Choon Chua, Beng; Hnin Wut Yi, Su; Yang, Yili; Urbanik, Andrzej

2015-01-01

Our objective was to construct a 3D, interactive, and reference atlas of the extracranial vasculature spatially correlated with the intracranial blood vessels, cranial nerves, skull, glands, and head muscles. The atlas has been constructed from multiple 3T and 7T magnetic resonance angiogram (MRA) brain scans, and 3T phase contrast and inflow MRA neck scans of the same specimen in the following steps: vessel extraction from the scans, building 3D tubular models of the vessels, spatial registration of the extra- and intracranial vessels, vessel editing, vessel naming and color-coding, vessel simplification, and atlas validation. This new atlas contains 48 names of the extracranial vessels (25 arterial and 23 venous) and it has been integrated with the existing brain atlas. The atlas is valuable for medical students and residents to easily get familiarized with the extracranial vasculature with a few clicks; is useful for educators to prepare teaching materials; and potentially can serve as a reference in the diagnosis of vascular disease and treatment, including craniomaxillofacial surgeries and radiologic interventions of the face and neck. PMID:25923683

Astronauts Gardner and Allen during loading of Palapa B-2 in payload bay

NASA Image and Video Library

1984-11-12

51A-41-058 (12 November 1984) --- Astronaut Joseph P. Allen IV appears to be lifting weights. Astronaut Dale A. Gardner holding on. Actually, Dr. Allen is the sole anchor for the top portion (and most of) the captured Palapa B-2 communications satellite during the Nov. 12 retrieval extravehicular activity (EVA) of the two mission specialists. This scene came near the end of the long-duration task. Gardner used a torque wrench to tighten clamps on an adapter used to secure the Palapa to its "parking place" in Discovery's cargo bay. Note the difference between the two stinger devices stowed on Challenger's port side (right side of frame). The one nearer the spacecraft's vertical stabilizer is spent, having been inserted by Allen earlier in the day to stabilize the communications satellite. The one nearer the camera awaited duty in two days when it would aid in the capture of the Westar VI satellite.

A Summing Up. Allen Memorial Art Museum Addition, Oberlin, Ohio

ERIC Educational Resources Information Center

Progressive Architecture, 1977

1977-01-01

Venturi and Rauch's addition to the Allen Art Museum at Oberlin College is in two separate parts: a loft that houses new facilities for the art department and a gallery for contemporary art. (Author/MLF)

Cobalt/rhodium heterobimetallic nanoparticle-catalyzed carbonylative [2+2+1] cycloaddition of allenes and bisallenes to Pauson-Khand-type reaction products.

PubMed

Park, Ji Hoon; Kim, Eunha; Kim, Hyeong-Mook; Choi, Soo Young; Chung, Young Keun

2008-05-28

The first catalytic intra- and intermolecular [2+2+1] cocyclization reactions of allenes and carbon monoxide have been developed. In the Co(2)Rh(2) heterobimetallic nanoparticle-catalyzed carbonylative [2+2+1] cycloaddition of allenes and carbon monoxide, the allenes formally serve both as an excellent alkene- and alkyne-like moiety within a Pauson-Khand-type process.

An image registration pipeline for analysis of transsynaptic tracing in mice

NASA Astrophysics Data System (ADS)

Kutten, Kwame S.; Eacker, Stephen M.; Dawson, Valina L.; Dawson, Ted M.; Ratnanather, Tilak; Miller, Michael I.

2016-03-01

Parkinson's Disease (PD) is a movement disorder characterized by the loss of dopamine neurons in the substantia nigra pars compacta (SNpc) and norepinephrine neurons in the locus coeruleus (LC). To further understand the pathophysiology of PD, the input neurons of the SNpc and LC will be transsynapticly traced in mice using a fluorescent recombinant rabies virus (RbV) and imaged using serial two-photon tomography (STP). A mapping between these images and a brain atlas must be found to accurately determine the locations of input neurons in the brain. Therefore a registration pipeline to align the Allen Reference Atlas (ARA) to these types of images was developed. In the preprocessing step, a brain mask was generated from the transsynaptic tracing images using simple morphological operators. The masks were then registered to the ARA using Large Deformation Diffeomorphic Metric Mapping (LDDMM), an algorithm specialized for calculating anatomically realistic transforms between images. The pipeline was then tested on an STP scan of a mouse brain labeled by an adeno-associated virus (AAV). Based on qualitative evaluation of the registration results, the pipeline was found to be sufficient for use with transsynaptic RbV tracing.

Catlas: An magnetic resonance imaging-based three-dimensional cortical atlas and tissue probability maps for the domestic cat (Felis catus).

PubMed

Stolzberg, Daniel; Wong, Carmen; Butler, Blake E; Lomber, Stephen G

2017-10-15

Brain atlases play an important role in effectively communicating results from neuroimaging studies in a standardized coordinate system. Furthermore, brain atlases extend analysis of functional magnetic resonance imaging (MRI) data by delineating regions of interest over which to evaluate the extent of functional activation as well as measures of inter-regional connectivity. Here, we introduce a three-dimensional atlas of the cat cerebral cortex based on established cytoarchitectonic and electrophysiological findings. In total, 71 cerebral areas were mapped onto the gray matter (GM) of an averaged T1-weighted structural MRI acquired at 7 T from eight adult domestic cats. In addition, a nonlinear registration procedure was used to generate a common template brain as well as GM, white matter, and cerebral spinal fluid tissue probability maps to facilitate tissue segmentation as part of the standard preprocessing pipeline for MRI data analysis. The atlas and associated files can also be used for planning stereotaxic surgery and for didactic purposes. © 2017 Wiley Periodicals, Inc.

STS-75 Mission Commander Andrew M. Allen in White Room

NASA Technical Reports Server (NTRS)

1996-01-01

STS-75 Mission Commander Andrew M. Allen (center) prepares to enter the Space Shuttle Columbia at Launch Pad 39B with assistance from white room closeout crew members Paul Arnold (left), Dave Law and Bob Saulnier.

Cross-scale observations of the 2015 St. Patrick's day storm: THEMIS, Van Allen Probes, and TWINS

DOE PAGES

Goldstein, J.; Angelopoulos, V.; De Pascuale, S.; ...

2016-12-10

In this paper, we present cross-scale magnetospheric observations of the 17 March 2015 (St. Patrick's Day) storm, by Time History of Events and Macroscale Interactions during Substorms (THEMIS), Van Allen Probes (Radiation Belt Storm Probes), and Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS), plus upstream ACE/Wind solar wind data. THEMIS crossed the bow shock or magnetopause 22 times and observed the magnetospheric compression that initiated the storm. Empirical models reproduce these boundary locations within 0.7 R E. Van Allen Probes crossed the plasmapause 13 times; test particle simulations reproduce these encounters within 0.5 R E. Before the storm, Van Allen Probesmore » measured quiet double-nose proton spectra in the region of corotating cold plasma. About 15 min after a 0605 UT dayside southward turning, Van Allen Probes captured the onset of inner magnetospheric convection, as a density decrease at the moving corotation-convection boundary (CCB) and a steep increase in ring current (RC) proton flux. During the first several hours of the storm, Van Allen Probes measured highly dynamic ion signatures (numerous injections and multiple spectral peaks). Sustained convection after ~1200 UT initiated a major buildup of the midnight-sector ring current (measured by RBSP A), with much weaker duskside fluxes (measured by RBSP B, THEMIS a and THEMIS d). A close conjunction of THEMIS d, RBSP A, and TWINS 1 at 1631 UT shows good three-way agreement in the shapes of two-peak spectra from the center of the partial RC. A midstorm injection, observed by Van Allen Probes and TWINS at 1740 UT, brought in fresh ions with lower average energies (leading to globally less energetic spectra in precipitating ions) but increased the total pressure. Finally, the cross-scale measurements of 17 March 2015 contain significant spatial, spectral, and temporal structure.« less

Generation of EMIC Waves Observed by Van Allen Probes at Low L-shells of Earth's Magnetosphere

NASA Astrophysics Data System (ADS)

Gamayunov, K. V.; Zhang, J.; Saikin, A.; Rassoul, H.

2017-12-01

In a multi-ion magnetospheric plasma, where the major species are H+, He+, and O+, the He-band of electromagnetic ion cyclotron (EMIC) waves is the dominant band observed in the inner magnetosphere, and waves are generally quasi-field-aligned inside the geostationary orbit. Almost all the satellite-based studies of EMIC waves before Van Allen Probes, however, have not reported waves below L 3.5. There is probably only one exception from the Akebono satellite where both the H-band and He-band EMIC waves were observed at L 2. The situation has changed dramatically after two Van Allen Probes spacecraft were launched on 30 August, 2012, and many EMIC wave events have been observed below L=4. The Van Allen Probes observations confirm that the He-band of EMIC waves is a dominant band in the inner magnetosphere, but the observation of the He-band waves below L=4 is a new and quite unexpected result compared to our knowledge about EMIC waves before the Van Allen Probes era. In addition, observations show that almost all the He-band EMIC waves are linearly polarized in the region L < 4. This result is also new and unexpected. Here we will present an observational test of the generation mechanism for the He-band EMIC waves observed by Van Allen Probes at L 2.8 on 18 March, 2013. All the plasma parameters, DC magnetic field, and energetic ion distribution functions will be taken from the Van Allen Probes observations during the EMIC wave event to calculate growth rates of EMIC waves. We will then identify the energetic ions responsible for instability, frequencies and normals generated, and physical mechanism of instability.

Cross-scale observations of the 2015 St. Patrick's day storm: THEMIS, Van Allen Probes, and TWINS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldstein, J.; Angelopoulos, V.; De Pascuale, S.

In this paper, we present cross-scale magnetospheric observations of the 17 March 2015 (St. Patrick's Day) storm, by Time History of Events and Macroscale Interactions during Substorms (THEMIS), Van Allen Probes (Radiation Belt Storm Probes), and Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS), plus upstream ACE/Wind solar wind data. THEMIS crossed the bow shock or magnetopause 22 times and observed the magnetospheric compression that initiated the storm. Empirical models reproduce these boundary locations within 0.7 R E. Van Allen Probes crossed the plasmapause 13 times; test particle simulations reproduce these encounters within 0.5 R E. Before the storm, Van Allen Probesmore » measured quiet double-nose proton spectra in the region of corotating cold plasma. About 15 min after a 0605 UT dayside southward turning, Van Allen Probes captured the onset of inner magnetospheric convection, as a density decrease at the moving corotation-convection boundary (CCB) and a steep increase in ring current (RC) proton flux. During the first several hours of the storm, Van Allen Probes measured highly dynamic ion signatures (numerous injections and multiple spectral peaks). Sustained convection after ~1200 UT initiated a major buildup of the midnight-sector ring current (measured by RBSP A), with much weaker duskside fluxes (measured by RBSP B, THEMIS a and THEMIS d). A close conjunction of THEMIS d, RBSP A, and TWINS 1 at 1631 UT shows good three-way agreement in the shapes of two-peak spectra from the center of the partial RC. A midstorm injection, observed by Van Allen Probes and TWINS at 1740 UT, brought in fresh ions with lower average energies (leading to globally less energetic spectra in precipitating ions) but increased the total pressure. Finally, the cross-scale measurements of 17 March 2015 contain significant spatial, spectral, and temporal structure.« less

Commentary on Sowcik and Allen: Getting Down to Business

ERIC Educational Resources Information Center

Murphy, Susan Elaine

2013-01-01

Sowcik and Allen's paper, "Getting Down to Business: A Look at Leadership Education in Business Schools," identifies a number of compelling issues in improving leadership education in business schools and provides a thorough overview of how these efforts could benefit from the considerations present in the National Leadership Educators…

Astronaut Andrew Allen monitors Columbia's systems from pilots station

NASA Image and Video Library

1994-03-05

STS062-41-025 (18 March 1994) --- Astronaut Andrew M. Allen monitors Columbia's systems from the pilot's station during the entry phase of the STS-62 mission. The fast-speed 35mm film highlights the many controls and displays and the cathode ray tubes on the forward flight deck.

Spacecraft surface charging within geosynchronous orbit observed by the Van Allen Probes

DOE PAGES

Sarno-Smith, Lois K.; Larsen, Brian A.; Skoug, Ruth M.; ...

2016-02-27

Using the Helium Oxygen Proton Electron (HOPE) and Electric Field and Waves (EFW) instruments from the Van Allen Probes, we explored the relationship between electron energy fluxes in the eV and keV ranges and spacecraft surface charging. We present statistical results on spacecraft charging within geosynchronous orbit by L and MLT. An algorithm to extract the H+ charging line in the HOPE instrument data was developed to better explore intense charging events. Also, this study explored how spacecraft potential relates to electron number density, electron pressure, electron temperature, thermal electron current, and low-energy ion density between 1 and 210 eV.more » It is demonstrated that it is imperative to use both EFW potential measurements and the HOPE instrument ion charging line for examining times of extreme spacecraft charging of the Van Allen Probes. The results of this study show that elevated electron energy fluxes and high-electron pressures are present during times of spacecraft charging but these same conditions may also occur during noncharging times. Furthermore, we also show noneclipse significant negative charging events on the Van Allen Probes.« less

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.

PubMed

Yee, Yohan; Fernandes, Darren J; French, Leon; Ellegood, Jacob; Cahill, Lindsay S; Vousden, Dulcie A; Spencer Noakes, Leigh; Scholz, Jan; van Eede, Matthijs C; Nieman, Brian J; Sled, John G; Lerch, Jason P

2018-05-18

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the

Association of Protein Distribution and Gene Expression Revealed by PET and Post-Mortem Quantification in the Serotonergic System of the Human Brain

PubMed Central

Komorowski, A.; James, G. M.; Philippe, C.; Gryglewski, G.; Bauer, A.; Hienert, M.; Spies, M.; Kautzky, A.; Vanicek, T.; Hahn, A.; Traub-Weidinger, T.; Winkler, D.; Wadsak, W.; Mitterhauser, M.; Hacker, M.; Kasper, S.; Lanzenberger, R.

2017-01-01

Abstract Regional differences in posttranscriptional mechanisms may influence in vivo protein densities. The association of positron emission tomography (PET) imaging data from 112 healthy controls and gene expression values from the Allen Human Brain Atlas, based on post-mortem brains, was investigated for key serotonergic proteins. PET binding values and gene expression intensities were correlated for the main inhibitory (5-HT1A) and excitatory (5-HT2A) serotonin receptor, the serotonin transporter (SERT) as well as monoamine oxidase-A (MAO-A), using Spearman's correlation coefficients (rs) in a voxel-wise and region-wise analysis. Correlations indicated a strong linear relationship between gene and protein expression for both the 5-HT1A (voxel-wise rs = 0.71; region-wise rs = 0.93) and the 5-HT2A receptor (rs = 0.66; 0.75), but only a weak association for MAO-A (rs = 0.26; 0.66) and no clear correlation for SERT (rs = 0.17; 0.29). Additionally, region-wise correlations were performed using mRNA expression from the HBT, yielding comparable results (5-HT1Ars = 0.82; 5-HT2Ars = 0.88; MAO-A rs = 0.50; SERT rs = −0.01). The SERT and MAO-A appear to be regulated in a region-specific manner across the whole brain. In contrast, the serotonin-1A and -2A receptors are presumably targeted by common posttranscriptional processes similar in all brain areas suggesting the applicability of mRNA expression as surrogate parameter for density of these proteins. PMID:27909009

Automated atlas-based clustering of white matter fiber tracts from DTMRI.

PubMed

Maddah, Mahnaz; Mewes, Andrea U J; Haker, Steven; Grimson, W Eric L; Warfield, Simon K

2005-01-01

A new framework is presented for clustering fiber tracts into anatomically known bundles. This work is motivated by medical applications in which variation analysis of known bundles of fiber tracts in the human brain is desired. To include the anatomical knowledge in the clustering, we invoke an atlas of fiber tracts, labeled by the number of bundles of interest. In this work, we construct such an atlas and use it to cluster all fiber tracts in the white matter. To build the atlas, we start with a set of labeled ROIs specified by an expert and extract the fiber tracts initiating from each ROI. Affine registration is used to project the extracted fiber tracts of each subject to the atlas, whereas their B-spline representation is used to efficiently compare them to the fiber tracts in the atlas and assign cluster labels. Expert visual inspection of the result confirms that the proposed method is very promising and efficient in clustering of the known bundles of fiber tracts.

EnviroAtlas - Austin, TX - Atlas Area Boundary

EPA Pesticide Factsheets

This EnviroAtlas dataset shows the boundary of the Austin, TX Atlas Area. It represents the outside edge of all the block groups included in the EnviroAtlas Area.This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Automated liver segmentation using a normalized probabilistic atlas

NASA Astrophysics Data System (ADS)

Linguraru, Marius George; Li, Zhixi; Shah, Furhawn; Chin, See; Summers, Ronald M.

2009-02-01

Probabilistic atlases of anatomical organs, especially the brain and the heart, have become popular in medical image analysis. We propose the construction of probabilistic atlases which retain structural variability by using a size-preserving modified affine registration. The organ positions are modeled in the physical space by normalizing the physical organ locations to an anatomical landmark. In this paper, a liver probabilistic atlas is constructed and exploited to automatically segment liver volumes from abdominal CT data. The atlas is aligned with the patient data through a succession of affine and non-linear registrations. The overlap and correlation with manual segmentations are 0.91 (0.93 DICE coefficient) and 0.99 respectively. Little work has taken place on the integration of volumetric measures of liver abnormality to clinical evaluations, which rely on linear estimates of liver height. Our application measures the liver height at the mid-hepatic line (0.94 correlation with manual measurements) and indicates that its combination with volumetric estimates could assist the development of a noninvasive tool to assess hepatomegaly.

Three-dimensional stereotactic atlas of the extracranial vasculature correlated with the intracranial vasculature, cranial nerves, skull and muscles.

PubMed

Nowinski, Wieslaw L; Shoon Let Thaung, Thant; Choon Chua, Beng; Hnin Wut Yi, Su; Yang, Yili; Urbanik, Andrzej

2015-04-01

Our objective was to construct a 3D, interactive, and reference atlas of the extracranial vasculature spatially correlated with the intracranial blood vessels, cranial nerves, skull, glands, and head muscles.The atlas has been constructed from multiple 3T and 7T magnetic resonance angiogram (MRA) brain scans, and 3T phase contrast and inflow MRA neck scans of the same specimen in the following steps: vessel extraction from the scans, building 3D tubular models of the vessels, spatial registration of the extra- and intracranial vessels, vessel editing, vessel naming and color-coding, vessel simplification, and atlas validation.This new atlas contains 48 names of the extracranial vessels (25 arterial and 23 venous) and it has been integrated with the existing brain atlas.The atlas is valuable for medical students and residents to easily get familiarized with the extracranial vasculature with a few clicks; is useful for educators to prepare teaching materials; and potentially can serve as a reference in the diagnosis of vascular disease and treatment, including craniomaxillofacial surgeries and radiologic interventions of the face and neck. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

[A study on Horace N. Allen's medicine and recognition of Korean body].

PubMed

Lee, Young Ah

2011-12-31

Je Jung Won was the first modern-style Government hospital built by the Korean King Ko-Jong in April 1885, and it was the medical missionary Horace Newton Allen(1858~1932) who made one of the greatest contributions to the establishment of the hospital. Allen was an American missionary. He graduated from Ohio Wesleyan University with a degree in theology in 1881, and completed one-yearcourse at Miami Medical College. In Korea and America he worked as a physician, a missionary, an American diplomatic minister to Korea and a Korean minister's secretary to America. While acting as a mediator between Korea and America, he knew and recorded the domestic and foreign situation of Korea during Gaehwagi(the civilized and enlightened age). Thus to study him is to understand Korea's Gaehwagi as well as to research American medical missionaries. During his stay in Korea(1884~1905), Allen steadily wrote diaries and letters about Korean politics, diplomacy, society, culture, and medicine. Thus his public/private record through diaries and letters(the quantity of these materials amounts to several thousands) supplements the Korean early modern era's historical record. However, until now these materials have received little scholarly attention from researchers except for a few historians of missionary work between Korea and America, or of Korean modern medicine. I intended to use these materials to suggest a new perspective on the study of Korean Gaehwagi. Allen, along with John W. Heron, who came to Seoul on June 21st 1885, treated about 10,460 Korean patients in the first year of the opening of JeJungWon. They made "the first annual report of the Korean Government Hospital". This report explained how Allen and Heron regarded and treated Korean patients. Allen's diaries, letters and other writings offer a realistic view of how the western people actually recognized the Korean people at that time. As a western doctor, Allen had an ambivalent attitude toward Korean medical concepts

Spatial and temporal characterization of relativistic electron enhancements during the Van Allen Probes era.

NASA Astrophysics Data System (ADS)

Pinto, V. A.; Sibeck, D. G.; Moya, P. S.; Lyons, L. R.; Kanekal, S. G.; Kletzing, C.

2016-12-01

During the Van Allen probes era from September 2012 to June 2016 we have identified 53 relativistic electron enhancement events determined by increases to 2x103 #/sr-1}s{-1}cm^{-2 and above in the >2 MeV electron fluxes at geostationary orbit as measured by the GOES 13 and 15 Energetic Particle Sensor (EPS) instrument. Using the Van Allen Probes ECT-REPT and GOES EPS instruments we have characterized the radial and temporal profiles of the events, grouping them according to how the increases propagate radially. Using OMNI data we have studied the statistical properties of the solar wind for each group of events and have classified similarities and differences that might be relevant for each enhancement profile. We have also studied temporal and spatial wave activity (ULF and EMIC waves) using GOES magnetometer data and Van Allen Probes EMFISIS data for the different groups of events and categorized the appearance of such waves for the different enhancement profiles.

Cortical Enhanced Tissue Segmentation of Neonatal Brain MR Images Acquired by a Dedicated Phased Array Coil

PubMed Central

Shi, Feng; Yap, Pew-Thian; Fan, Yong; Cheng, Jie-Zhi; Wald, Lawrence L.; Gerig, Guido; Lin, Weili; Shen, Dinggang

2010-01-01

The acquisition of high quality MR images of neonatal brains is largely hampered by their characteristically small head size and low tissue contrast. As a result, subsequent image processing and analysis, especially for brain tissue segmentation, are often hindered. To overcome this problem, a dedicated phased array neonatal head coil is utilized to improve MR image quality by effectively combing images obtained from 8 coil elements without lengthening data acquisition time. In addition, a subject-specific atlas based tissue segmentation algorithm is specifically developed for the delineation of fine structures in the acquired neonatal brain MR images. The proposed tissue segmentation method first enhances the sheet-like cortical gray matter (GM) structures in neonatal images with a Hessian filter for generation of cortical GM prior. Then, the prior is combined with our neonatal population atlas to form a cortical enhanced hybrid atlas, which we refer to as the subject-specific atlas. Various experiments are conducted to compare the proposed method with manual segmentation results, as well as with additional two population atlas based segmentation methods. Results show that the proposed method is capable of segmenting the neonatal brain with the highest accuracy, compared to other two methods. PMID:20862268

Astronaut Andrew M. Allen monitors Columbia's systems from pilots station

NASA Technical Reports Server (NTRS)

1994-01-01

Astronaut Andrew M. Allen monitors Columbia's systems from the pilot's station during the entry phase of the STS-62 mission. The fast-speed 35mm film highlights the many controls and displays and the cathode ray tubes on the forward flight deck.

Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.

PubMed

Bricq, S; Collet, Ch; Armspach, J P

2008-12-01

In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. Here-proposed method takes into account neighborhood information using a Hidden Markov Chain (HMC) model. Due to the limited resolution of imaging devices, voxels may be composed of a mixture of different tissue types, this partial volume effect is included to achieve an accurate segmentation of brain tissues. Instead of assigning each voxel to a single tissue class (i.e., hard classification), we compute the relative amount of each pure tissue class in each voxel (mixture estimation). Further, a bias field estimation step is added to the proposed algorithm to correct intensity inhomogeneities. Furthermore, atlas priors were incorporated using probabilistic brain atlas containing prior expectations about the spatial localization of different tissue classes. This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.

Learning to rank atlases for multiple-atlas segmentation.

PubMed

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Shen, Dinggang

2014-10-01

Recently, multiple-atlas segmentation (MAS) has achieved a great success in the medical imaging area. The key assumption is that multiple atlases have greater chances of correctly labeling a target image than a single atlas. However, the problem of atlas selection still remains unexplored. Traditionally, image similarity is used to select a set of atlases. Unfortunately, this heuristic criterion is not necessarily related to the final segmentation performance. To solve this seemingly simple but critical problem, we propose a learning-based atlas selection method to pick up the best atlases that would lead to a more accurate segmentation. Our main idea is to learn the relationship between the pairwise appearance of observed instances (i.e., a pair of atlas and target images) and their final labeling performance (e.g., using the Dice ratio). In this way, we select the best atlases based on their expected labeling accuracy. Our atlas selection method is general enough to be integrated with any existing MAS method. We show the advantages of our atlas selection method in an extensive experimental evaluation in the ADNI, SATA, IXI, and LONI LPBA40 datasets. As shown in the experiments, our method can boost the performance of three widely used MAS methods, outperforming other learning-based and image-similarity-based atlas selection methods.

In Silico Prediction and Validation of Gfap as an miR-3099 Target in Mouse Brain.

PubMed

Abidin, Shahidee Zainal; Leong, Jia-Wen; Mahmoudi, Marzieh; Nordin, Norshariza; Abdullah, Syahril; Cheah, Pike-See; Ling, King-Hwa

2017-08-01

MicroRNAs are small non-coding RNAs that play crucial roles in the regulation of gene expression and protein synthesis during brain development. MiR-3099 is highly expressed throughout embryogenesis, especially in the developing central nervous system. Moreover, miR-3099 is also expressed at a higher level in differentiating neurons in vitro, suggesting that it is a potential regulator during neuronal cell development. This study aimed to predict the target genes of miR-3099 via in-silico analysis using four independent prediction algorithms (miRDB, miRanda, TargetScan, and DIANA-micro-T-CDS) with emphasis on target genes related to brain development and function. Based on the analysis, a total of 3,174 miR-3099 target genes were predicted. Those predicted by at least three algorithms (324 genes) were subjected to DAVID bioinformatics analysis to understand their overall functional themes and representation. The analysis revealed that nearly 70% of the target genes were expressed in the nervous system and a significant proportion were associated with transcriptional regulation and protein ubiquitination mechanisms. Comparison of in situ hybridization (ISH) expression patterns of miR-3099 in both published and in-house-generated ISH sections with the ISH sections of target genes from the Allen Brain Atlas identified 7 target genes (Dnmt3a, Gabpa, Gfap, Itga4, Lxn, Smad7, and Tbx18) having expression patterns complementary to miR-3099 in the developing and adult mouse brain samples. Of these, we validated Gfap as a direct downstream target of miR-3099 using the luciferase reporter gene system. In conclusion, we report the successful prediction and validation of Gfap as an miR-3099 target gene using a combination of bioinformatics resources with enrichment of annotations based on functional ontologies and a spatio-temporal expression dataset.

A Century after Van Allen's Birth: Conclusion of Reconnaissance of Radiation Belts in the Solar System

NASA Astrophysics Data System (ADS)

Krimigis, S. M.

2014-12-01

On May 1, 1958 in the Great Hall of the US National Academy of Sciences, James A. Van Allen, having instrumented Explorer-1 and follow-on satellites with radiation detectors, announced the discovery of intense radiation at high altitudes above Earth. The press dubbed the doughnut-shaped structures "Van Allen Belts" (VAB). Soon thereafter, the search began for VAB at nearby planets. Mariner 2 flew by Venus in 1962 at a distance of 41,000 km, but no radiation was detected. The Mariner 4 mission to Mars did not observe planet-associated increase in radiation, but scaling arguments with Earth's magnetosphere yielded an upper limit to the ratio of magnetic moments of MM/ME < 0.001 (Van Allen et al, 1965). Similarly, the Mariner 5 flyby closer to Venus resulted in a ratio of magnetic moments < 0.001 (Van Allen et al, 1967), dealing a blow to the expectation that all planetary bodies must possess significant VAB. The flyby of Mercury in 1974 by Mariner 10 revealed a weak magnetic field, but the presence of durably trapped higher energy particles remained controversial until MESSENGER in 2011.The first flybys of Jupiter by Pioneers 10, 11 in 1973 and 1974, respectively, measured a plethora of energetic particles in Jupiter's magnetosphere and established the fact that their intensities were rotationally modulated. Later flybys of Jupiter and Saturn by the two Voyagers in 1979 and 1981 revealed that those magnetospheres possessed their own internal plasma source(s) and radiation belts. Subsequent discoveries of Van Allen belts at Uranus and Neptune by Voyager 2 demonstrated that VAB are the rule rather than the exception in planetary environments. We now know from the Voyagers and through Energetic Neutral Atom images from Cassini and IBEX that an immense energetic particle population surrounds the heliosphere itself. Thus, the reconnaissance of radiation belts of our solar system has been completed, some 56 years after the discovery of the Van Allen Belts at Earth.

Convergence Analysis of the Graph Allen-Cahn Scheme

DTIC Science & Technology

2016-02-01

CONVERGENCE ANALYSIS OF THE GRAPH ALLEN-CAHN SCHEME ∗ XIYANG LUO† AND ANDREA L. BERTOZZI† Abstract. Graph partitioning problems have a wide range of...optimization, convergence and monotonicity are shown for a class of schemes under a graph-independent timestep restriction. We also analyze the effects of...spectral truncation, a common technique used to save computational cost. Convergence of the scheme with spectral truncation is also proved under a

Transcriptional Landscape of the Prenatal Human Brain

PubMed Central

Miller, Jeremy A.; Ding, Song-Lin; Sunkin, Susan M.; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L.; Aiona, Kaylynn; Arnold, James M.; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A.; Dee, Nick; Dolbeare, Tim A.; Facer, Benjamin A. C.; Feng, David; Fliss, Tim P.; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W.; Gu, Guangyu; Howard, Robert E.; Jochim, Jayson M.; Kuan, Chihchau L.; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A.; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick F.; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D.; Parry, Sheana E.; Player, Allison Stevens; Pletikos, Mihovil; Reding, Melissa; Royall, Joshua J.; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V.; Shen, Elaine H.; Sjoquist, Nathan; Slaughterbeck, Clifford R.; Smith, Michael; Sodt, Andy J.; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B.; Geschwind, Daniel H.; Glass, Ian A.; Hawrylycz, Michael J.; Hevner, Robert F.; Huang, Hao; Jones, Allan R.; Knowles, James A.; Levitt, Pat; Phillips, John W.; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G.; Lein, Ed S.

2014-01-01

Summary The anatomical and functional architecture of the human brain is largely determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and postmitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and human-expanded outer subventricular zones. Both germinal and postmitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in frontal lobe. Finally, many neurodevelopmental disorder and human evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development. PMID:24695229

Transcriptional landscape of the prenatal human brain.

PubMed

Miller, Jeremy A; Ding, Song-Lin; Sunkin, Susan M; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L; Royall, Joshua J; Aiona, Kaylynn; Arnold, James M; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A; Dee, Nick; Dolbeare, Tim A; Facer, Benjamin A C; Feng, David; Fliss, Tim P; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W; Gu, Guangyu; Howard, Robert E; Jochim, Jayson M; Kuan, Chihchau L; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D; Parry, Sheana E; Stevens, Allison; Pletikos, Mihovil; Reding, Melissa; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V; Shen, Elaine H; Sjoquist, Nathan; Slaughterbeck, Clifford R; Smith, Michael; Sodt, Andy J; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B; Geschwind, Daniel H; Glass, Ian A; Hawrylycz, Michael J; Hevner, Robert F; Huang, Hao; Jones, Allan R; Knowles, James A; Levitt, Pat; Phillips, John W; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G; Lein, Ed S

2014-04-10

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

Mites associated with southern pine bark beetles in Allen Parish, Louisiana

Treesearch

John C. Moser; Lawrence M. Roton

1971-01-01

Ninety-six species of mites were associated with the southern pine beetle and allied scolytids in an outbreak area in Allen Parish, La. the complex was evaluated to ascertain which species may be of value as biological control agents.

Mites associated with Southern Pine Bark Beetles in Allen Parish, Louisiana

Treesearch

John C. Moser; Lawrence M. Roton

1971-01-01

Ninety-six species of mites were associated with the southern pine beetle and allied scolytides in an outbreak area in Allen Parish, LA. The complex was evaluated to ascertain which species may be of value as biological control agents.

Evaluation of effects of groundwater withdrawals at the proposed Allen combined-cycle combustion turbine plant, Shelby County, Tennessee

USGS Publications Warehouse

Haugh, Connor J.

2016-08-10

The Mississippi Embayment Regional Aquifer Study groundwater-flow model was used to simulate the potential effects of future groundwater withdrawals at the proposed Allen combined-cycle combustion turbine plant in Shelby County, Tennessee. The scenario used in the simulation consisted of a 30-year average withdrawal period followed by a 30-day maximum withdrawal period. Effects of withdrawals at the Allen plant site on the Mississippi embayment aquifer system were evaluated by comparing the difference in simulated water levels in the aquifers at the end of the 30-year average withdrawal period and at the end of the scenario to a base case without the Allen combined-cycle combustion turbine plant withdrawals. Simulated potentiometric surface declines in the Memphis aquifer at the Allen plant site were about 7 feet at the end of the 30-year average withdrawal period and 11 feet at the end of the scenario. The affected area of the Memphis aquifer at the Allen plant site as delineated by the 4-foot potentiometric surface-decline contour was 2,590 acres at the end of the 30-year average withdrawal period and 11,380 acres at the end of the scenario. Simulated declines in the underlying Fort Pillow aquifer and overlying shallow aquifer were both less than 1 foot at the end of the 30-year average withdrawal period and the end of the scenario.

Intraoperative virtual brain counseling

NASA Astrophysics Data System (ADS)

Jiang, Zhaowei; Grosky, William I.; Zamorano, Lucia J.; Muzik, Otto; Diaz, Fernando

1997-06-01

Our objective is to offer online real-tim e intelligent guidance to the neurosurgeon. Different from traditional image-guidance technologies that offer intra-operative visualization of medical images or atlas images, virtual brain counseling goes one step further. It can distinguish related brain structures and provide information about them intra-operatively. Virtual brain counseling is the foundation for surgical planing optimization and on-line surgical reference. It can provide a warning system that alerts the neurosurgeon if the chosen trajectory will pass through eloquent brain areas. In order to fulfill this objective, tracking techniques are involved for intra- operativity. Most importantly, a 3D virtual brian environment, different from traditional 3D digitized atlases, is an object-oriented model of the brain that stores information about different brain structures together with their elated information. An object-oriented hierarchical hyper-voxel space (HHVS) is introduced to integrate anatomical and functional structures. Spatial queries based on position of interest, line segment of interest, and volume of interest are introduced in this paper. The virtual brain environment is integrated with existing surgical pre-planning and intra-operative tracking systems to provide information for planning optimization and on-line surgical guidance. The neurosurgeon is alerted automatically if the planned treatment affects any critical structures. Architectures such as HHVS and algorithms, such as spatial querying, normalizing, and warping are presented in the paper. A prototype has shown that the virtual brain is intuitive in its hierarchical 3D appearance. It also showed that HHVS, as the key structure for virtual brain counseling, efficiently integrates multi-scale brain structures based on their spatial relationships.This is a promising development for optimization of treatment plans and online surgical intelligent guidance.

Semi-automated quantification and neuroanatomical mapping of heterogeneous cell populations.

PubMed

Mendez, Oscar A; Potter, Colin J; Valdez, Michael; Bello, Thomas; Trouard, Theodore P; Koshy, Anita A

2018-07-15

Our group studies the interactions between cells of the brain and the neurotropic parasite Toxoplasma gondii. Using an in vivo system that allows us to permanently mark and identify brain cells injected with Toxoplasma protein, we have identified that Toxoplasma-injected neurons (TINs) are heterogeneously distributed throughout the brain. Unfortunately, standard methods to quantify and map heterogeneous cell populations onto a reference brain atlas are time consuming and prone to user bias. We developed a novel MATLAB-based semi-automated quantification and mapping program to allow the rapid and consistent mapping of heterogeneously distributed cells on to the Allen Institute Mouse Brain Atlas. The system uses two-threshold background subtraction to identify and quantify cells of interest. We demonstrate that we reliably quantify and neuroanatomically localize TINs with low intra- or inter-observer variability. In a follow up experiment, we show that specific regions of the mouse brain are enriched with TINs. The procedure we use takes advantage of simple immunohistochemistry labeling techniques, use of a standard microscope with a motorized stage, and low cost computing that can be readily obtained at a research institute. To our knowledge there is no other program that uses such readily available techniques and equipment for mapping heterogeneous populations of cells across the whole mouse brain. The quantification method described here allows reliable visualization, quantification, and mapping of heterogeneous cell populations in immunolabeled sections across whole mouse brains. Copyright © 2018 Elsevier B.V. All rights reserved.

Arthroscopic Medial Meniscus Posterior Root Fixation Using a Modified Mason-Allen Stitch.

PubMed

Chung, Kyu Sung; Ha, Jeong Ku; Ra, Ho Jong; Kim, Jin Goo

2016-02-01

A complete radial tear of the meniscus posterior root, which can effectively cause a state of total meniscectomy via loss of hoop tension, requires that the torn root be repaired. Several methods have been used to repair medial meniscus posterior root tears, most of which are based on a simple stitch technique that is known to have stitch-holding strength. We applied a modified version of the Mason-Allen stitch technique, which is recognized as a method for rotator cuff repair surgery because its locking effect overcomes the potential weakness of simple stitches. This article introduces the medial meniscus posterior root tears repair procedure based on a modified Mason-Allen stitch technique in which 2 strands (i.e., 1 simple horizontal and 1 simple vertical stitch) are used.

STS-75 Mission Cmdr Andrew Allen arrives at SLF

NASA Technical Reports Server (NTRS)

1996-01-01

STS-75 Mission Commander Andrew M. Allen arrives at KSC's Shuttle Landing Facility. Altogether seven crew members are assigned to the second Shuttle flight of 1996, which will be highlighted by the re-flight of the Italian Tethered Satellite System (TSS-1R). Liftoff is slated to occur during a two-and-a-half window opening at 3:18 p.m. EST, Feb. 22.

Multi atlas based segmentation: Should we prefer the best atlas group over the group of best atlases?

PubMed

Zaffino, Paolo; Ciardo, Delia; Raudaschl, Patrik; Fritscher, Karl; Ricotti, Rosalinda; Alterio, Daniela; Marvaso, Giulia; Fodor, Cristiana; Baroni, Guido; Amato, Francesco; Orecchia, Roberto; Jereczek-Fossa, Barbara Alicja; Sharp, Gregory C; Spadea, Maria Francesca

2018-05-22

Multi Atlas Based Segmentation (MABS) uses a database of atlas images, and an atlas selection process is used to choose an atlas subset for registration and voting. In the current state of the art, atlases are chosen according to a similarity criterion between the target subject and each atlas in the database. In this paper, we propose a new concept for atlas selection that relies on selecting the best performing group of atlases rather than the group of highest scoring individual atlases. Experiments were performed using CT images of 50 patients, with contours of brainstem and parotid glands. The dataset was randomly split in 2 groups: 20 volumes were used as an atlas database and 30 served as target subjects for testing. Classic oracle group selection, where atlases are chosen by the highest Dice Similarity Coefficient (DSC) with the target, was performed. This was compared to oracle Group selection, where all the combinations of atlas subgroups were considered and scored by computing DSC with the target subject. Subsequently, Convolutional Neural Networks (CNNs) were designed to predict the best group of atlases. The results were compared also with the selection strategy based on Normalized Mutual Information (NMI). Oracle group was proved to be significantly better that classic oracle selection (p<10-5). Atlas group selection led to a median±interquartile DSC of 0.740±0.084, 0.718±0.086 and 0.670±0.097 for brainstem and left/right parotid glands respectively, outperforming NMI selection 0.676±0.113, 0.632±0.104 and 0.606±0.118 (p<0.001) as well as classic oracle selection. The implemented methodology is a proof of principle that selecting the atlases by considering the performance of the entire group of atlases instead of each single atlas leads to higher segmentation accuracy, being even better then current oracle strategy. This finding opens a new discussion about the most appropriate atlas selection criterion for MABS. © 2018

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

Atlas-based identification of targets for functional radiosurgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stancanello, Joseph; Romanelli, Pantaleo; Modugno, Nicola

2006-06-15

Functional disorders of the brain, such as Parkinson's disease, dystonia, epilepsy, and neuropathic pain, may exhibit poor response to medical therapy. In such cases, surgical intervention may become necessary. Modern surgical approaches to such disorders include radio-frequency lesioning and deep brain stimulation (DBS). The subthalamic nucleus (STN) is one of the most useful stereotactic targets available: STN DBS is known to induce substantial improvement in patients with end-stage Parkinson's disease. Other targets include the Globus Pallidus pars interna (GPi) for dystonia and Parkinson's disease, and the centromedian nucleus of the thalamus (CMN) for neuropathic pain. Radiosurgery is an attractive noninvasivemore » alternative to treat some functional brain disorders. The main technical limitation to radiosurgery is that the target can be selected only on the basis of magnetic resonance anatomy without electrophysiological confirmation. The aim of this work is to provide a method for the correct atlas-based identification of the target to be used in functional neurosurgery treatment planning. The coordinates of STN, CMN, and GPi were identified in the Talairach and Tournoux atlas and transformed to the corresponding regions of the Montreal Neurological Institute (MNI) electronic atlas. Binary masks describing the target nuclei were created. The MNI electronic atlas was deformed onto the patient magnetic resonance imaging-T1 scan by applying an affine transformation followed by a local nonrigid registration. The first transformation was based on normalized cross correlation and the second on optimization of a two-part objective function consisting of similarity criteria and weighted regularization. The obtained deformation field was then applied to the target masks. The minimum distance between the surface of an implanted electrode and the surface of the deformed mask was calculated. The validation of the method consisted of comparing the electrode

MRIVIEW: An interactive computational tool for investigation of brain structure and function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ranken, D.; George, J.

MRIVIEW is a software system which uses image processing and visualization to provide neuroscience researchers with an integrated environment for combining functional and anatomical information. Key features of the software include semi-automated segmentation of volumetric head data and an interactive coordinate reconciliation method which utilizes surface visualization. The current system is a precursor to a computational brain atlas. We describe features this atlas will incorporate, including methods under development for visualizing brain functional data obtained from several different research modalities.

Investigation into 9(S)-HPODE-derived allene oxide to cyclopentenone cyclization mechanism via diradical oxyallyl intermediates

PubMed Central

Hebert, Sebastien P.; Cha, Jin K.; Brash, Alan R.; Schlegel, H. Bernhard

2016-01-01

The cyclopentane core is ubiquitous among a large number of biologically relevant natural products. Cyclopentenones have been shown to be versatile intermediates for the stereoselective preparation of highly substituted cyclopentane derivatives. Allene oxides are oxygenated fatty acids which are involved in the pathways of cyclopentenone biosynthesis in plants and marine invertebrates; however, their cyclization behavior is not well understood. Recent work by Brash and co-workers (J. Biol. Chem. 2013, 288, 20797) revealed an unusual cyclization property of the 9(S)-HPODE-derived allene oxides: the previously unreported 10Z-isomer cyclizes to a cis-dialkylcyclopentenone in hexane/isopropyl alcohol (100:3,v/v), but the known 10E-isomer does not yield cis-cyclopentenone under the same conditions. The mechanism for cyclization has been investigated for unsubstituted and methyl substituted vinyl allene oxide using a variety of methods including CASSCF, ωB97xD, and CCSD(T) and basis sets up to cc-pVTZ. The lowest energy pathway proceeds via homolytic cleavage of the epoxide ring, formation of an oxyallyl diradical, which closes readily to a cyclopropanone intermediate. The cyclopropanone opens to the requisite oxyallyl which closes to the experimentally observed product, cis-cyclopentenone. The calculations show that the open shell, diradical pathway is lower in energy than the closed shell reactions of allene oxide to cyclopropanone, and cyclopropanone to cyclopentenone. PMID:26976802

Arthroscopic modified Mason-Allen technique for large U- or L-shaped rotator cuff tears.

PubMed

Jung, Sung-Weon; Kim, Dong-Hee; Kang, Seung-Hoon; Lee, Ji-Heon

2017-07-01

While a conventional single- or double-row repair technique could be applied for repair of C-shaped tears, a different surgical strategy should be considered for repair of U- or L-shaped tears because they typically have complex patterns with anterior, posterior, or both mobile leaves. This study was performed to examine the outcomes of the modified Mason-Allen technique for footprint restoration in the treatment of large U- or L-shaped rotator cuff tears. Thirty-two patients who underwent an arthroscopic modified Mason-Allen technique for large U- or L-shaped rotator cuff tears between January 2012 and December 2013 were included in this study. Margin convergence was first performed to reduce the tear gap and tension, and then, an arthroscopic Mason-Allen technique was performed to restore the rotator cuff footprint in a side-to-end repair fashion. All patients were evaluated preoperatively and for a minimum of 2 years of follow-up with a visual analog scale (VAS) for pain, Constant score, and ultrasonography. There was significant improvement in all VAS and Constant scores compared with the preoperative values (P < 0.001). Functional results by Constant scores included 9 cases that were classified as excellent, 11 cases as good, 8 cases as fair, and 2 cases as poor. Binary logistic regression analysis revealed that heavy work, pseudoparalysis, joint space narrowing, fatty degeneration of the SST and IST, and a positive tangent sign were found to significantly correlate with functional outcomes. Multivariable logistic regression analysis revealed that only fatty degeneration of the SST was a risk factor for fair/poor clinical outcomes. Complications occurred in 5 of the 32 patients (15.6 %), and the reoperation rate due to complications was 6.3 % (2 of 32 patients). An arthroscopic modified Mason-Allen technique was sufficient to restore the footprint of the rotator cuff in our data. Overall satisfactory results were achieved in most patients, with the

Atlas Fractures and Atlas Osteosynthesis: A Comprehensive Narrative Review.

PubMed

Kandziora, Frank; Chapman, Jens R; Vaccaro, Alexander R; Schroeder, Gregory D; Scholz, Matti

2017-09-01

Most atlas fractures are the result of compression forces. They are often combined with fractures of the axis and especially with the odontoid process. Multiple classification systems for atlas fractures have been described. For an adequate diagnosis, a computed tomography is mandatory. To distinguish between stable and unstable atlas injury, it is necessary to evaluate the integrity of the transverse atlantal ligament (TAL) by magnetic resonance imaging and to classify the TAL lesion. Studies comparing conservative and operative management of unstable atlas fractures are unfortunately not available in the literature; neither are studies comparing different operative treatment strategies. Hence all treatment recommendations are based on low level evidence. Most of atlas fractures are stable and will be successfully managed by immobilization in a soft/hard collar. Unstable atlas fractures may be treated conservatively by halo-fixation, but nowadays more and more surgeons prefer surgery because of the potential discomfort and complications of halo-traction. Atlas fractures with a midsubstance ligamentous disruption of TAL or severe bony ligamentous avulsion can be treated by a C1/2 fusion. Unstable atlas fractures with moderate bony ligamentous avulsion may be treated by atlas osteosynthesis. Although the evidence for the different treatment strategies of atlas fractures is low, atlas osteosynthesis has the potential to change treatment philosophies. The reasons for this are described in this review.

Astronauts Gemar and Allen work with lower body negative pressure experiment

NASA Image and Video Library

1994-03-05

STS062-07-010 (4-18 March 1994) --- Astronaut Andrew M. Allen, pilot, participates in biomedical testing as he does a "soak" in the Lower Body Negative Pressure (LBNP) apparatus on the Columbia's middeck. Astronaut Charles D. (Sam) Gemar, mission specialist, monitors readouts from the test.

All Together Now: Valerie Allen--U.S. Department of Energy

ERIC Educational Resources Information Center

Library Journal, 2005

2005-01-01

When Valerie Allen decided she did not want to be a Montessori teacher any longer, she began work on her MLIS. Immediately she learned concepts she could apply to her new job as information specialist for the Department of Energy's (DOE) Office of Scientific and Technical Information (OSTI) at Oak Ridge National Laboratory, TN. While the LIS…

A Neural Network Approach for Identifying Particle Pitch Angle Distributions in Van Allen Probes Data

NASA Technical Reports Server (NTRS)

Souza, V. M.; Vieira, L. E. A.; Medeiros, C.; Da Silva, L. A.; Alves, L. R.; Koga, D.; Sibeck, D. G.; Walsh, B. M.; Kanekal, S. G.; Jauer, P. R.;

Gradual Diffusion and Punctuated Phase Space Density Enhancements of Highly Relativistic Electrons: Van Allen Probes Observations

NASA Technical Reports Server (NTRS)

Baker, D. N.; Jaynes, A. N.; Li, X.; Henderson, M. G.; Kanekal, S. G.; Reeves, G. D.; Spence, H. E.; Claudepierre, S. G.; Fennell, J. F.; Hudson, M. K.

2014-01-01

The dual-spacecraft Van Allen Probes mission has provided a new window into mega electron volt (MeV) particle dynamics in the Earth's radiation belts. Observations (up to E (is) approximately 10MeV) show clearly the behavior of the outer electron radiation belt at different timescales: months-long periods of gradual inward radial diffusive transport and weak loss being punctuated by dramatic flux changes driven by strong solar wind transient events. We present analysis of multi-MeV electron flux and phase space density (PSD) changes during March 2013 in the context of the first year of Van Allen Probes operation. This March period demonstrates the classic signatures both of inward radial diffusive energization and abrupt localized acceleration deep within the outer Van Allen zone (L (is) approximately 4.0 +/- 0.5). This reveals graphically that both 'competing' mechanisms of multi-MeV electron energization are at play in the radiation belts, often acting almost concurrently or at least in rapid succession.

Stimulation sites in the subthalamic nucleus projected onto a mean 3-D atlas of the thalamus and basal ganglia.

PubMed

Sarnthein, Johannes; Péus, Dominik; Baumann-Vogel, Heide; Baumann, Christian R; Sürücü, Oguzkan

2013-09-01

In patients with severe forms of Parkinson's disease (PD), deep brain stimulation (DBS) commonly targets the subthalamic nucleus (STN). Recently, the mean 3-D Morel-Atlas of the basal ganglia and the thalamus was introduced. It combines information contained in histological data from ten post-mortem brains. We were interested whether the Morel-Atlas is applicable for the visualization of stimulation sites. In a consecutive PD patient series, we documented preoperative MRI planning, intraoperative target adjustment based on electrophysiological and neurological testing, and perioperative CT target reconstruction. The localization of the DBS electrodes and the optimal stimulation sites were projected onto the Morel-Atlas. We included 20 patients (median age 62 years). The active contact had mean coordinates Xlat = ±12.1 mm, Yap = -1.8 mm, Zvert = -3.2 mm. There was a significant difference between the initially planned site and the coordinates of the postoperative active contact site (median 2.2 mm). The stimulation site was, on average, more anterior and more dorsal. The electrode contact used for optimal stimulation was found within the STN of the atlas in 38/40 (95 %) of implantations. The cluster of stimulation sites in individual patients-as deduced from preoperative MR, intraoperative electrophysiology and neurological testing-showed a high degree of congruence with the atlas. The mean 3D Morel Atlas is thus a useful tool for postoperative target visualization. This represents the first clinical evaluation of the recently created atlas.

Subcortical structure segmentation using probabilistic atlas priors

NASA Astrophysics Data System (ADS)

Gouttard, Sylvain; Styner, Martin; Joshi, Sarang; Smith, Rachel G.; Cody Hazlett, Heather; Gerig, Guido

2007-03-01

The segmentation of the subcortical structures of the brain is required for many forms of quantitative neuroanatomic analysis. The volumetric and shape parameters of structures such as lateral ventricles, putamen, caudate, hippocampus, pallidus and amygdala are employed to characterize a disease or its evolution. This paper presents a fully automatic segmentation of these structures via a non-rigid registration of a probabilistic atlas prior and alongside a comprehensive validation. Our approach is based on an unbiased diffeomorphic atlas with probabilistic spatial priors built from a training set of MR images with corresponding manual segmentations. The atlas building computes an average image along with transformation fields mapping each training case to the average image. These transformation fields are applied to the manually segmented structures of each case in order to obtain a probabilistic map on the atlas. When applying the atlas for automatic structural segmentation, an MR image is first intensity inhomogeneity corrected, skull stripped and intensity calibrated to the atlas. Then the atlas image is registered to the image using an affine followed by a deformable registration matching the gray level intensity. Finally, the registration transformation is applied to the probabilistic maps of each structures, which are then thresholded at 0.5 probability. Using manual segmentations for comparison, measures of volumetric differences show high correlation with our results. Furthermore, the dice coefficient, which quantifies the volumetric overlap, is higher than 62% for all structures and is close to 80% for basal ganglia. The intraclass correlation coefficient computed on these same datasets shows a good inter-method correlation of the volumetric measurements. Using a dataset of a single patient scanned 10 times on 5 different scanners, reliability is shown with a coefficient of variance of less than 2 percents over the whole dataset. Overall, these validation

4D Infant Cortical Surface Atlas Construction using Spherical Patch-based Sparse Representation.

PubMed

Wu, Zhengwang; Li, Gang; Meng, Yu; Wang, Li; Lin, Weili; Shen, Dinggang

2017-09-01

The 4D infant cortical surface atlas with densely sampled time points is highly needed for neuroimaging analysis of early brain development. In this paper, we build the 4D infant cortical surface atlas firstly covering 6 postnatal years with 11 time points (i.e., 1, 3, 6, 9, 12, 18, 24, 36, 48, 60, and 72 months), based on 339 longitudinal MRI scans from 50 healthy infants. To build the 4D cortical surface atlas, first , we adopt a two-stage groupwise surface registration strategy to ensure both longitudinal consistency and unbiasedness. Second , instead of simply averaging over the co-registered surfaces, a spherical patch-based sparse representation is developed to overcome possible surface registration errors across different subjects. The central idea is that, for each local spherical patch in the atlas space, we build a dictionary, which includes the samples of current local patches and their spatially-neighboring patches of all co-registered surfaces, and then the current local patch in the atlas is sparsely represented using the built dictionary. Compared to the atlas built with the conventional methods, the 4D infant cortical surface atlas constructed by our method preserves more details of cortical folding patterns, thus leading to boosted accuracy in registration of new infant cortical surfaces.

Allene formation by gold catalyzed cross-coupling of masked carbenes and vinylidenes

PubMed Central

Lavallo, Vincent; Frey, Guido D.; Kousar, Shazia; Donnadieu, Bruno; Bertrand, Guy

2007-01-01

Addition of a sterically demanding cyclic (alkyl)(amino)carbene (CAAC) to AuCl(SMe2) followed by treatment with [Et3Si(Tol)]+[B(C6F5)4]− in toluene affords the isolable [(CAAC)Au(η2-toluene)]+[B(C6F5)4]− complex. This cationic Au(I) complex efficiently mediates the catalytic coupling of enamines and terminal alkynes to yield allenes and not propargyl amines as observed with other catalysts. Mono-, di-, and tri-substituted enamines can be used, as well as aryl-, alkyl-, and trimethylsilyl-substituted terminal alkynes. The reaction tolerates sterically hindered substrates and is diastereoselective. This general catalytic protocol directly couples two unsaturated carbon centers to form the three-carbon allenic core. The reaction most probably proceeds through an unprecedented “carbene/vinylidene cross-coupling.” PMID:17698808

Crystallization and Preliminary X-ray Analysis of Allene Oxide Synthase, Cytochrome P450 CYP74A2, from Parthenium argentatum

USDA-ARS?s Scientific Manuscript database

Oxylipins are oxygenated derivatives of fatty acids and pivotal signaling molecules in plants and animals. Allene oxide synthase (AOS) is a key cytochrome P450 CYP74 enzyme involved in the biosynthesis of plant oxylipin jasmonates to convert 13(S)-hydroperoxide to allene oxide. Guayule (Parthenium a...

'Whose atlas I use, his song I sing?' - The impact of anatomical atlases on fiber tract contributions to cognitive deficits after stroke.

PubMed

de Haan, Bianca; Karnath, Hans-Otto

2017-12-01

Nowadays, different anatomical atlases exist for the anatomical interpretation of the results from neuroimaging and lesion analysis studies that investigate the contribution of white matter fiber tract integrity to cognitive (dys)function. A major problem with the use of different atlases in different studies, however, is that the anatomical interpretation of neuroimaging and lesion analysis results might vary as a function of the atlas used. This issue might be particularly prominent in studies that investigate the contribution of white matter fiber tract integrity to cognitive (dys)function. We used a single large-sample dataset of right brain damaged stroke patients with and without cognitive deficit (here: spatial neglect) to systematically compare the influence of three different, widely-used white matter fiber tract atlases (1 histology-based atlas and 2 DTI tractography-based atlases) on conclusions concerning the involvement of white matter fiber tracts in the pathogenesis of cognitive dysfunction. We both calculated the overlap between the statistical lesion analysis results and each long association fiber tract (topological analyses) and performed logistic regressions on the extent of fiber tract damage in each individual for each long association white matter fiber tract (hodological analyses). For the topological analyses, our results suggest that studies that use tractography-based atlases are more likely to conclude that white matter integrity is critical for a cognitive (dys)function than studies that use a histology-based atlas. The DTI tractography-based atlases classified approximately 10 times as many voxels of the statistical map as being located in a long association white matter fiber tract than the histology-based atlas. For hodological analyses on the other hand, we observed that the conclusions concerning the overall importance of long association fiber tract integrity to cognitive function do not necessarily depend on the white matter

TU-AB-BRA-02: An Efficient Atlas-Based Synthetic CT Generation Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, X

2016-06-15

Purpose: A major obstacle for MR-only radiotherapy is the need to generate an accurate synthetic CT (sCT) from MR image(s) of a patient for the purposes of dose calculation and DRR generation. We propose here an accurate and efficient atlas-based sCT generation method, which has a computation speed largely independent of the number of atlases used. Methods: Atlas-based sCT generation requires a set of atlases with co-registered CT and MR images. Unlike existing methods that align each atlas to the new patient independently, we first create an average atlas and pre-align every atlas to the average atlas space. When amore » new patient arrives, we compute only one deformable image registration to align the patient MR image to the average atlas, which indirectly aligns the patient to all pre-aligned atlases. A patch-based non-local weighted fusion is performed in the average atlas space to generate the sCT for the patient, which is then warped back to the original patient space. We further adapt a PatchMatch algorithm that can quickly find top matches between patches of the patient image and all atlas images, which makes the patch fusion step also independent of the number of atlases used. Results: Nineteen brain tumour patients with both CT and T1-weighted MR images are used as testing data and a leave-one-out validation is performed. Each sCT generated is compared against the original CT image of the same patient on a voxel-by-voxel basis. The proposed method produces a mean absolute error (MAE) of 98.6±26.9 HU overall. The accuracy is comparable with a conventional implementation scheme, but the computation time is reduced from over an hour to four minutes. Conclusion: An average atlas space patch fusion approach can produce highly accurate sCT estimations very efficiently. Further validation on dose computation accuracy and using a larger patient cohort is warranted. The author is a full time employee of Elekta, Inc.« less

JAtlasView: a Java atlas-viewer for browsing biomedical 3D images and atlases.

PubMed

Feng, Guangjie; Burton, Nick; Hill, Bill; Davidson, Duncan; Kerwin, Janet; Scott, Mark; Lindsay, Susan; Baldock, Richard

2005-03-09

Many three-dimensional (3D) images are routinely collected in biomedical research and a number of digital atlases with associated anatomical and other information have been published. A number of tools are available for viewing this data ranging from commercial visualization packages to freely available, typically system architecture dependent, solutions. Here we discuss an atlas viewer implemented to run on any workstation using the architecture neutral Java programming language. We report the development of a freely available Java based viewer for 3D image data, descibe the structure and functionality of the viewer and how automated tools can be developed to manage the Java Native Interface code. The viewer allows arbitrary re-sectioning of the data and interactive browsing through the volume. With appropriately formatted data, for example as provided for the Electronic Atlas of the Developing Human Brain, a 3D surface view and anatomical browsing is available. The interface is developed in Java with Java3D providing the 3D rendering. For efficiency the image data is manipulated using the Woolz image-processing library provided as a dynamically linked module for each machine architecture. We conclude that Java provides an appropriate environment for efficient development of these tools and techniques exist to allow computationally efficient image-processing libraries to be integrated relatively easily.

7T MRI subthalamic nucleus atlas for use with 3T MRI.

PubMed

Milchenko, Mikhail; Norris, Scott A; Poston, Kathleen; Campbell, Meghan C; Ushe, Mwiza; Perlmutter, Joel S; Snyder, Abraham Z

2018-01-01

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces motor symptoms in most patients with Parkinson disease (PD), yet may produce untoward effects. Investigation of DBS effects requires accurate localization of the STN, which can be difficult to identify on magnetic resonance images collected with clinically available 3T scanners. The goal of this study is to develop a high-quality STN atlas that can be applied to standard 3T images. We created a high-definition STN atlas derived from seven older participants imaged at 7T. This atlas was nonlinearly registered to a standard template representing 56 patients with PD imaged at 3T. This process required development of methodology for nonlinear multimodal image registration. We demonstrate mm-scale STN localization accuracy by comparison of our 3T atlas with a publicly available 7T atlas. We also demonstrate less agreement with an earlier histological atlas. STN localization error in the 56 patients imaged at 3T was less than 1 mm on average. Our methodology enables accurate STN localization in individuals imaged at 3T. The STN atlas and underlying 3T average template in MNI space are freely available to the research community. The image registration methodology developed in the course of this work may be generally applicable to other datasets.

Diels–Alder Reactions of Allene with Benzene and Butadiene: Concerted, Stepwise, and Ambimodal Transition States

PubMed Central

2015-01-01

Multiconfigurational complete active space methods (CASSCF and CASPT2) have been used to investigate the (4 + 2) cycloadditions of allene with butadiene and with benzene. Both concerted and stepwise radical pathways were examined to determine the mechanism of the Diels–Alder reactions with an allene dienophile. Reaction with butadiene occurs via a single ambimodal transition state that can lead to either the concerted or stepwise trajectories along the potential energy surface, while reaction with benzene involves two separate transition states and favors the concerted mechanism relative to the stepwise mechanism via a diradical intermediate. PMID:25216056

A multi-object statistical atlas adaptive for deformable registration errors in anomalous medical image segmentation

NASA Astrophysics Data System (ADS)

Botter Martins, Samuel; Vallin Spina, Thiago; Yasuda, Clarissa; Falcão, Alexandre X.

2017-02-01

Statistical Atlases have played an important role towards automated medical image segmentation. However, a challenge has been to make the atlas more adaptable to possible errors in deformable registration of anomalous images, given that the body structures of interest for segmentation might present significant differences in shape and texture. Recently, deformable registration errors have been accounted by a method that locally translates the statistical atlas over the test image, after registration, and evaluates candidate objects from a delineation algorithm in order to choose the best one as final segmentation. In this paper, we improve its delineation algorithm and extend the model to be a multi-object statistical atlas, built from control images and adaptable to anomalous images, by incorporating a texture classifier. In order to provide a first proof of concept, we instantiate the new method for segmenting, object-by-object and all objects simultaneously, the left and right brain hemispheres, and the cerebellum, without the brainstem, and evaluate it on MRT1-images of epilepsy patients before and after brain surgery, which removed portions of the temporal lobe. The results show efficiency gain with statistically significant higher accuracy, using the mean Average Symmetric Surface Distance, with respect to the original approach.

Measuring specific receptor binding of a PET radioligand in human brain without pharmacological blockade: The genomic plot.

PubMed

Veronese, Mattia; Zanotti-Fregonara, Paolo; Rizzo, Gaia; Bertoldo, Alessandra; Innis, Robert B; Turkheimer, Federico E

2016-04-15

PET studies allow in vivo imaging of the density of brain receptor species. The PET signal, however, is the sum of the fraction of radioligand that is specifically bound to the target receptor and the non-displaceable fraction (i.e. the non-specifically bound radioligand plus the free ligand in tissue). Therefore, measuring the non-displaceable fraction, which is generally assumed to be constant across the brain, is a necessary step to obtain regional estimates of the specific fractions. The nondisplaceable binding can be directly measured if a reference region, i.e. a region devoid of any specific binding, is available. Many receptors are however widely expressed across the brain, and a true reference region is rarely available. In these cases, the nonspecific binding can be obtained after competitive pharmacological blockade, which is often contraindicated in humans. In this work we introduce the genomic plot for estimating the nondisplaceable fraction using baseline scans only. The genomic plot is a transformation of the Lassen graphical method in which the brain maps of mRNA transcripts of the target receptor obtained from the Allen brain atlas are used as a surrogate measure of the specific binding. Thus, the genomic plot allows the calculation of the specific and nondisplaceable components of radioligand uptake without the need of pharmacological blockade. We first assessed the statistical properties of the method with computer simulations. Then we sought ground-truth validation using human PET datasets of seven different neuroreceptor radioligands, where nonspecific fractions were either obtained separately using drug displacement or available from a true reference region. The population nondisplaceable fractions estimated by the genomic plot were very close to those measured by actual human blocking studies (mean relative difference between 2% and 7%). However, these estimates were valid only when mRNA expressions were predictive of protein levels (i

Measuring specific receptor binding of a PET radioligand in human brain without pharmacological blockade: The genomic plot

PubMed Central

Veronese, Mattia; Zanotti-Fregonara, Paolo; Rizzo, Gaia; Bertoldo, Alessandra; Innis, Robert B.; Turkheimer, Federico E.

2016-01-01

PET studies allow in vivo imaging of the density of brain receptor species. The PET signal, however, is the sum of the fraction of radioligand that is specifically bound to the target receptor and the non-displaceable fraction (i.e. the non-specifically bound radioligand plus the free ligand in tissue). Therefore, measuring the non-displaceable fraction, which is generally assumed to be constant across the brain, is a necessary step to obtain regional estimates of the specific fractions. The nondisplaceable binding can be directly measured if a reference region, i.e. a region devoid of any specific binding, is available. Many receptors are however widely expressed across the brain, and a true reference region is rarely available. In these cases, the nonspecific binding can be obtained after competitive pharmacological blockade, which is often contraindicated in humans. In this work we introduce the genomic plot for estimating the nondisplaceable fraction using baseline scans only. The genomic plot is a transformation of the Lassen graphical method in which the brain maps of mRNA transcripts of the target receptor obtained from the Allen brain atlas are used as a surrogate measure of the specific binding. Thus, the genomic plot allows the calculation of the specific and nondisplaceable components of radioligand uptake without the need of pharmacological blockade. We first assessed the statistical properties of the method with computer simulations. Then we sought ground-truth validation using human PET datasets of seven different neuroreceptor radioligands, where nonspecific fractions were either obtained separately using drug displacement or available from a true reference region. The population nondisplaceable fractions estimated by the genomic plot were very close to those measured by actual human blocking studies (mean relative difference between 2% and 7%). However, these estimates were valid only when mRNA expressions were predictive of protein levels (i

Computer tomographic imaging and anatomic correlation of the human brain: A comparative atlas of thin CT-scan sections and correlated neuro-anatomic preparations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plets, C.; Baert, A.L.; Nijs, G.L.

1986-01-01

It is of the greatest importance to the radiologist, the neurologist and the neurosurgeon to be able to localize topographically a pathological brain process on the CT scan as precisely as possible. For that purpose, the identification of as many anatomical structures as possible on the CT scan image are necessary and indispensable. In this atlas a great number of detailed anatomical data on frontal horizontal CT scan sections, each being only 2 mm thick, are indicated, e.g. the cortical gyri, the basal ganglia, details of the white matter, extracranial muscles and blood vessels, parts of the base and themore » vault of the skull, etc. The very precise topographical description of the numerous CT scan images was realized by the author by confrontation of these images with the corresponding anatomical sections of the same brain specimen, performed by an original technique.« less

ExAtlas: An interactive online tool for meta-analysis of gene expression data.

PubMed

Sharov, Alexei A; Schlessinger, David; Ko, Minoru S H

2015-12-01

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users' own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher's methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein-protein interaction) are pre-loaded and can be used for functional annotations.

An allene oxide and 12-oxophytodienoic acid are key intermediates in jasmonic acid biosynthesis by Fusarium oxysporum.

PubMed

Oliw, Ernst H; Hamberg, Mats

2017-08-01

Fungi can produce jasmonic acid (JA) and its isoleucine conjugate in large quantities, but little is known about the biosynthesis. Plants form JA from 18:3 n -3 by 13 S -lipoxygenase (LOX), allene oxide synthase, and allene oxide cyclase. Shaking cultures of Fusarium oxysporum f. sp. tulipae released over 200 mg of jasmonates per liter. Nitrogen powder of the mycelia expressed 10 R -dioxygenase-epoxy alcohol synthase activities, which was confirmed by comparison with the recombinant enzyme. The 13 S -LOX of F. oxysporum could not be detected in the cell-free preparations. Incubation of mycelia in phosphate buffer with [17,17,18,18,18- 2 H 5 ]18:3 n -3 led to biosynthesis of a [ 2 H 5 ]12-oxo-13-hydroxy-9 Z ,15 Z -octadecadienoic acid (α-ketol), [ 2 H 5 ]12-oxo-10,15 Z -phytodienoic acid (12-OPDA), and [ 2 H 5 ]13-keto- and [ 2 H 5 ]13 S -hydroxyoctadecatrienoic acids. The α-ketol consisted of 90% of the 13 R stereoisomer, suggesting its formation by nonenzymatic hydrolysis of an allene oxide with 13 S configuration. Labeled and unlabeled 12-OPDA were observed following incubation with 0.1 mM [ 2 H 5 ]18:3 n -3 in a ratio from 0.4:1 up to 47:1 by mycelia of liquid cultures of different ages, whereas 10 times higher concentration of [ 2 H 5 ]13 S -hydroperoxyoctadecatrienoic acid was required to detect biosynthesis of [ 2 H 5 ]12-OPDA. The allene oxide is likely formed by a cytochrome P450 or catalase-related hydroperoxidase. We conclude that F. oxysporum , like plants, forms jasmonates with an allene oxide and 12-OPDA as intermediates. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.

STS-75 Mission Cmdr Andrew Allen talks to media

NASA Technical Reports Server (NTRS)

1996-01-01

STS-75 Mission Commander Andrew M. Allen talks to news media gathered at KSC's Shuttle Landing Facility for the flight crew's arrival. Altogether seven crew members are assigned to the second Shuttle flight of 1996, which will be highlighted by the re- flight of the Italian Tethered Satellite System (TSS-1R). Liftoff is slated to occur during a two-and-a-half window opening at 3:18 p.m. EST, Feb. 22.

An MRI-Based Atlas for Correlation of Imaging and Pathologic Findings in Alzheimer's Disease.

PubMed

Raman, Mekala R; Schwarz, Christopher G; Murray, Melissa E; Lowe, Val J; Dickson, Dennis W; Jack, Clifford R; Kantarci, Kejal

2016-05-01

Pathologic diagnosis is the gold standard in evaluating imaging measures developed as biomarkers for pathologically defined disorders. A brain MRI atlas representing autopsy-sampled tissue can be used to directly compare imaging and pathology findings. Our objective was to develop a brain MRI atlas representing the cortical regions that are routinely sampled at autopsy for the diagnosis of Alzheimer's disease (AD). Subjects (n = 22; ages at death = 70-95) with a range of pathologies and antemortem 3T MRI were included. Histology slides from 8 cortical regions sampled from the left hemisphere at autopsy guided the localization of the atlas regions of interest (ROIs) on each subject's antemortem 3D T1 -weighted MRI. These ROIs were then registered to a common template and combined to form one ROI representing the volume of tissue that was sampled by the pathologists. A subset of the subjects (n = 4; ages at death = 79-95) had amyloid PET imaging. Density of β-amyloid immunostain was quantified from the autopsy-sampled regions in the 4 subjects using a custom-designed ImageScope algorithm. Median uptake values were calculated in each ROI on the amyloid-PET images. We found an association between β-amyloid plaque density in 8 ROIs of the 4 subjects (total ROI n = 32) and median PiB SUVR (r(2) = .64; P < .0001). In an atlas developed for imaging and pathologic correlation studies, we demonstrated that antemortem amyloid burden measured in the atlas ROIs on amyloid PET is strongly correlated with β-amyloid density measured on histology. This atlas can be used in imaging and pathologic correlation studies. © 2016 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.

Gross feature recognition of Anatomical Images based on Atlas grid (GAIA): Incorporating the local discrepancy between an atlas and a target image to capture the features of anatomic brain MRI.

PubMed

Qin, Yuan-Yuan; Hsu, Johnny T; Yoshida, Shoko; Faria, Andreia V; Oishi, Kumiko; Unschuld, Paul G; Redgrave, Graham W; Ying, Sarah H; Ross, Christopher A; van Zijl, Peter C M; Hillis, Argye E; Albert, Marilyn S; Lyketsos, Constantine G; Miller, Michael I; Mori, Susumu; Oishi, Kenichi

2013-01-01

We aimed to develop a new method to convert T1-weighted brain MRIs to feature vectors, which could be used for content-based image retrieval (CBIR). To overcome the wide range of anatomical variability in clinical cases and the inconsistency of imaging protocols, we introduced the Gross feature recognition of Anatomical Images based on Atlas grid (GAIA), in which the local intensity alteration, caused by pathological (e.g., ischemia) or physiological (development and aging) intensity changes, as well as by atlas-image misregistration, is used to capture the anatomical features of target images. As a proof-of-concept, the GAIA was applied for pattern recognition of the neuroanatomical features of multiple stages of Alzheimer's disease, Huntington's disease, spinocerebellar ataxia type 6, and four subtypes of primary progressive aphasia. For each of these diseases, feature vectors based on a training dataset were applied to a test dataset to evaluate the accuracy of pattern recognition. The feature vectors extracted from the training dataset agreed well with the known pathological hallmarks of the selected neurodegenerative diseases. Overall, discriminant scores of the test images accurately categorized these test images to the correct disease categories. Images without typical disease-related anatomical features were misclassified. The proposed method is a promising method for image feature extraction based on disease-related anatomical features, which should enable users to submit a patient image and search past clinical cases with similar anatomical phenotypes.

Improving the Collection of Student Accounts at Allen County Community College.

ERIC Educational Resources Information Center

Geffert, Barbara

During the past several years, Allen County Community College has experienced a growing number of uncollected student accounts. In an effort to encourage timely payment of student charges, lower the number of students receiving payment deferments, increase cash flow at the beginning of each semester, and reduce the number of bad debts being…

Master Illustrator Allen Say Opens Students' Eyes to the Artist's Craft.

ERIC Educational Resources Information Center

Brehl, Sandy

2002-01-01

Discusses how the author uses Allen Say's picture storybooks to introduce intimidating (even to adults!) artistic language and concepts. Elaborates on several books that she used with her third-grade students. Demonstrates that a meaningful encounter with a skilled artist can change the way students see art in literary experiences and in their…

Magnetic resonance imaging of the pediatric brain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salamon, G.; Raynaud, C.; Regis, J.

1990-01-01

The atlas presents sequences of MRI sections parallel to the orbito-meatal plane in children from birth through the age of sixteen years. Each child was studied horizontally and sagitally and three-dimensional brain images were reconstructed to facilitate accurate identification of sulci and gyri. The images show crucial aspects of brain development such as the constancy of the brain stem and primitive brain from birth onward; the development of the telencephalon, characterized by deepening of sulci and growth of the cerebral cortex surface; and the different stages of white matter myelinization.

The role of image registration in brain mapping

PubMed Central

Toga, A.W.; Thompson, P.M.

2008-01-01

Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483

MARS: a mouse atlas registration system based on a planar x-ray projector and an optical camera

NASA Astrophysics Data System (ADS)

Wang, Hongkai; Stout, David B.; Taschereau, Richard; Gu, Zheng; Vu, Nam T.; Prout, David L.; Chatziioannou, Arion F.

2012-10-01

This paper introduces a mouse atlas registration system (MARS), composed of a stationary top-view x-ray projector and a side-view optical camera, coupled to a mouse atlas registration algorithm. This system uses the x-ray and optical images to guide a fully automatic co-registration of a mouse atlas with each subject, in order to provide anatomical reference for small animal molecular imaging systems such as positron emission tomography (PET). To facilitate the registration, a statistical atlas that accounts for inter-subject anatomical variations was constructed based on 83 organ-labeled mouse micro-computed tomography (CT) images. The statistical shape model and conditional Gaussian model techniques were used to register the atlas with the x-ray image and optical photo. The accuracy of the atlas registration was evaluated by comparing the registered atlas with the organ-labeled micro-CT images of the test subjects. The results showed excellent registration accuracy of the whole-body region, and good accuracy for the brain, liver, heart, lungs and kidneys. In its implementation, the MARS was integrated with a preclinical PET scanner to deliver combined PET/MARS imaging, and to facilitate atlas-assisted analysis of the preclinical PET images.

MARS: a mouse atlas registration system based on a planar x-ray projector and an optical camera.

PubMed

Wang, Hongkai; Stout, David B; Taschereau, Richard; Gu, Zheng; Vu, Nam T; Prout, David L; Chatziioannou, Arion F

2012-10-07

This paper introduces a mouse atlas registration system (MARS), composed of a stationary top-view x-ray projector and a side-view optical camera, coupled to a mouse atlas registration algorithm. This system uses the x-ray and optical images to guide a fully automatic co-registration of a mouse atlas with each subject, in order to provide anatomical reference for small animal molecular imaging systems such as positron emission tomography (PET). To facilitate the registration, a statistical atlas that accounts for inter-subject anatomical variations was constructed based on 83 organ-labeled mouse micro-computed tomography (CT) images. The statistical shape model and conditional Gaussian model techniques were used to register the atlas with the x-ray image and optical photo. The accuracy of the atlas registration was evaluated by comparing the registered atlas with the organ-labeled micro-CT images of the test subjects. The results showed excellent registration accuracy of the whole-body region, and good accuracy for the brain, liver, heart, lungs and kidneys. In its implementation, the MARS was integrated with a preclinical PET scanner to deliver combined PET/MARS imaging, and to facilitate atlas-assisted analysis of the preclinical PET images.

A New MRI Masking Technique Based on Multi-Atlas Brain Segmentation in Controls and Schizophrenia: A Rapid and Viable Alternative to Manual Masking.

PubMed

Del Re, Elisabetta C; Gao, Yi; Eckbo, Ryan; Petryshen, Tracey L; Blokland, Gabriëlla A M; Seidman, Larry J; Konishi, Jun; Goldstein, Jill M; McCarley, Robert W; Shenton, Martha E; Bouix, Sylvain

2016-01-01

Brain masking of MRI images separates brain from surrounding tissue and its accuracy is important for further imaging analyses. We implemented a new brain masking technique based on multi-atlas brain segmentation (MABS) and compared MABS to masks generated using FreeSurfer (FS; version 5.3), Brain Extraction Tool (BET), and Brainwash, using manually defined masks (MM) as the gold standard. We further determined the effect of different masking techniques on cortical and subcortical volumes generated by FreeSurfer. Images were acquired on a 3-Tesla MR Echospeed system General Electric scanner on five control and five schizophrenia subjects matched on age, sex, and IQ. Automated masks were generated from MABS, FS, BET, and Brainwash, and compared to MM using these metrics: a) volume difference from MM; b) Dice coefficients; and c) intraclass correlation coefficients. Mean volume difference between MM and MABS masks was significantly less than the difference between MM and FS or BET masks. Dice coefficient between MM and MABS was significantly higher than Dice coefficients between MM and FS, BET, or Brainwash. For subcortical and left cortical regions, MABS volumes were closer to MM volumes than were BET or FS volumes. For right cortical regions, MABS volumes were closer to MM volumes than were BET volumes. Brain masks generated using FreeSurfer, BET, and Brainwash are rapidly obtained, but are less accurate than manually defined masks. Masks generated using MABS, in contrast, resemble more closely the gold standard of manual masking, thereby offering a rapid and viable alternative. Copyright © 2015 by the American Society of Neuroimaging.

Transitional behavior of different energy protons based on Van Allen Probes observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Chao; Bortnik, Jacob; Chen, Lunjin

Understanding the dynamical behavior of ~1 eV to 50 keV ions and identifying the energies at which the morphologies transit are important in that they involve the relative intensities and distributions of the large-scale electric and magnetic fields, the outflow, and recombination rates. However, there have been only few direct observational investigations of the transition in drift behaviors of different energy ions before the Van Allen Probes era. In this paper, we statistically analyze ~1 eV to 50 keV hydrogen (H +) differential flux distributions near geomagnetic equator by using Van Allen Probes observations to investigate the H + dynamicsmore » under the regulation of large-scale electric and magnetic fields. Our survey clearly indicates three types of H + behaviors within different energy ranges, which is consistent with previous theory predictions. Finally, using simple electric and magnetic field models in UBK coordinates, we have further constrained the source regions of different energy ions and their drift directions.« less

Transitional behavior of different energy protons based on Van Allen Probes observations

DOE PAGES

Yue, Chao; Bortnik, Jacob; Chen, Lunjin; ...

2016-12-09

Understanding the dynamical behavior of ~1 eV to 50 keV ions and identifying the energies at which the morphologies transit are important in that they involve the relative intensities and distributions of the large-scale electric and magnetic fields, the outflow, and recombination rates. However, there have been only few direct observational investigations of the transition in drift behaviors of different energy ions before the Van Allen Probes era. In this paper, we statistically analyze ~1 eV to 50 keV hydrogen (H +) differential flux distributions near geomagnetic equator by using Van Allen Probes observations to investigate the H + dynamicsmore » under the regulation of large-scale electric and magnetic fields. Our survey clearly indicates three types of H + behaviors within different energy ranges, which is consistent with previous theory predictions. Finally, using simple electric and magnetic field models in UBK coordinates, we have further constrained the source regions of different energy ions and their drift directions.« less

Allylic and Allenic Halide Synthesis via NbCl5- and NbBr5-Mediated Alkoxide Rearrangements

PubMed Central

Ravikumar, P. C.; Yao, Lihua; Fleming, Fraser F.

2009-01-01

Addition of NbCl5, or NbBr5, to a series of magnesium, lithium, or potassium allylic or propargylic alkoxides directly provides allylic or allenic halides. Halogenation formally occurs through a metalla-halo-[3,3] rearrangement although concerted, ionic, and direct displacement mechanisms appear to operate competitively. Transposition of the olefin is equally effective for allylic alkoxides prepared by nucleophilic addition, deprotonation, or reduction. Experimentally, the niobium pentahalide halogenations are rapid, afford essentially pure E-allylic or allenic halides after extraction, and are applicable to a range of aliphatic and aromatic alcohols, aldehydes, and ketones. PMID:19739606

Gyri of the human parietal lobe: Volumes, spatial extents, automatic labelling, and probabilistic atlases

PubMed Central

Wild, Heather M.; Heckemann, Rolf A.; Studholme, Colin

2017-01-01

Accurately describing the anatomy of individual brains enables interlaboratory communication of functional and developmental studies and is crucial for possible surgical interventions. The human parietal lobe participates in multimodal sensory integration including language processing and also contains the primary somatosensory area. We describe detailed protocols to subdivide the parietal lobe, analyze morphological and volumetric characteristics, and create probabilistic atlases in MNI152 stereotaxic space. The parietal lobe was manually delineated on 3D T1 MR images of 30 healthy subjects and divided into four regions: supramarginal gyrus (SMG), angular gyrus (AG), superior parietal lobe (supPL) and postcentral gyrus (postCG). There was the expected correlation of male gender with larger brain and intracranial volume. We examined a wide range of anatomical features of the gyri and the sulci separating them. At least a rudimentary primary intermediate sulcus of Jensen (PISJ) separating SMG and AG was identified in nearly all (59/60) hemispheres. Presence of additional gyri in SMG and AG was related to sulcal features and volumetric characteristics. The parietal lobe was slightly (2%) larger on the left, driven by leftward asymmetries of the postCG and SMG. Intersubject variability was highest for SMG and AG, and lowest for postCG. Overall the morphological characteristics tended to be symmetrical, and volumes also tended to covary between hemispheres. This may reflect developmental as well as maturation factors. To assess the accuracy with which the labels can be used to segment newly acquired (unlabelled) T1-weighted brain images, we applied multi-atlas label propagation software (MAPER) in a leave-one-out experiment and compared the resulting automatic labels with the manually prepared ones. The results showed strong agreement (mean Jaccard index 0.69, corresponding to a mean Dice index of 0.82, average mean volume error of 0.6%). Stereotaxic probabilistic

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures.

PubMed

Lim, Issel Anne L; Faria, Andreia V; Li, Xu; Hsu, Johnny T C; Airan, Raag D; Mori, Susumu; van Zijl, Peter C M

2013-11-15

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a "deep gray matter parcellation map" (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established "white matter parcellation map" (WMPM) from the same subject's T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the "Everything Parcellation Map in Eve Space," also known as the "EvePM." It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting "almost perfect" agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures

PubMed Central

Lim, Issel Anne L.; Faria, Andreia V.; Li, Xu; Hsu, Johnny T.C.; Airan, Raag D.; Mori, Susumu; van Zijl, Peter C. M.

2013-01-01

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a “deep gray matter parcellation map” (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established “white matter parcellation map” (WMPM) from the same subject’s T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the “Everything Parcellation Map in Eve Space,” also known as the “EvePM.” It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting “almost perfect” agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron

Atlas of neuroanatomy with radiologic correlation and pathologic illustration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dublin, A.B.; Dublin, W.B.

1982-01-01

This atlas correlates gross neuroanatomic specimens with radiographs and computed tomographic scans. Pathologic specimens and radiographs are displayed in a similar manner. The first chapter, on embryology, shows the development of the telencephalon, diencephalon, mesencephalon, and metencephalon through a series of overlays. The anatomical section shows the surface of the brain, the ventricles and their adjacent structures, and the vascular system. CT anatomy is demonstrated by correlating CT scans with pathologic brain specimens cut in the axial plane. Pathologic changes associated with congenital malformations, injections, injuries, tumors, and other causes are demonstrated in the last six chapters.

Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases.

PubMed

Rondina, Jane Maryam; Ferreira, Luiz Kobuti; de Souza Duran, Fabio Luis; Kubo, Rodrigo; Ono, Carla Rachel; Leite, Claudia Costa; Smid, Jerusa; Nitrini, Ricardo; Buchpiguel, Carlos Alberto; Busatto, Geraldo F

2018-01-01

Machine learning techniques such as support vector machine (SVM) have been applied recently in order to accurately classify individuals with neuropsychiatric disorders such as Alzheimer's disease (AD) based on neuroimaging data. However, the multivariate nature of the SVM approach often precludes the identification of the brain regions that contribute most to classification accuracy. Multiple kernel learning (MKL) is a sparse machine learning method that allows the identification of the most relevant sources for the classification. By parcelating the brain into regions of interest (ROI) it is possible to use each ROI as a source to MKL (ROI-MKL). We applied MKL to multimodal neuroimaging data in order to: 1) compare the diagnostic performance of ROI-MKL and whole-brain SVM in discriminating patients with AD from demographically matched healthy controls and 2) identify the most relevant brain regions to the classification. We used two atlases (AAL and Brodmann's) to parcelate the brain into ROIs and applied ROI-MKL to structural (T1) MRI, 18 F-FDG-PET and regional cerebral blood flow SPECT (rCBF-SPECT) data acquired from the same subjects (20 patients with early AD and 18 controls). In ROI-MKL, each ROI received a weight (ROI-weight) that indicated the region's relevance to the classification. For each ROI, we also calculated whether there was a predominance of voxels indicating decreased or increased regional activity (for 18 F-FDG-PET and rCBF-SPECT) or volume (for T1-MRI) in AD patients. Compared to whole-brain SVM, the ROI-MKL approach resulted in better accuracies (with either atlas) for classification using 18 F-FDG-PET (92.5% accuracy for ROI-MKL versus 84% for whole-brain), but not when using rCBF-SPECT or T1-MRI. Although several cortical and subcortical regions contributed to discrimination, high ROI-weights and predominance of hypometabolism and atrophy were identified specially in medial parietal and temporo-limbic cortical regions. Also, the weight of

The NeuARt II system: a viewing tool for neuroanatomical data based on published neuroanatomical atlases

PubMed Central

Burns, Gully APC; Cheng, Wei-Cheng; Thompson, Richard H; Swanson, Larry W

2006-01-01

Background Anatomical studies of neural circuitry describing the basic wiring diagram of the brain produce intrinsically spatial, highly complex data of great value to the neuroscience community. Published neuroanatomical atlases provide a spatial framework for these studies. We have built an informatics framework based on these atlases for the representation of neuroanatomical knowledge. This framework not only captures current methods of anatomical data acquisition and analysis, it allows these studies to be collated, compared and synthesized within a single system. Results We have developed an atlas-viewing application ('NeuARt II') in the Java language with unique functional properties. These include the ability to use copyrighted atlases as templates within which users may view, save and retrieve data-maps and annotate them with volumetric delineations. NeuARt II also permits users to view multiple levels on multiple atlases at once. Each data-map in this system is simply a stack of vector images with one image per atlas level, so any set of accurate drawings made onto a supported atlas (in vector graphics format) could be uploaded into NeuARt II. Presently the database is populated with a corpus of high-quality neuroanatomical data from the laboratory of Dr Larry Swanson (consisting 64 highly-detailed maps of PHAL tract-tracing experiments, made up of 1039 separate drawings that were published in 27 primary research publications over 17 years). Herein we take selective examples from these data to demonstrate the features of NeuArt II. Our informatics tool permits users to browse, query and compare these maps. The NeuARt II tool operates within a bioinformatics knowledge management platform (called 'NeuroScholar') either as a standalone or a plug-in application. Conclusion Anatomical localization is fundamental to neuroscientific work and atlases provide an easily-understood framework that is widely used by neuroanatomists and non-neuroanatomists alike. Neu

Identifying aMCI with Functional Connectivity Network Characteristics based on Subtle AAL Atlas.

PubMed

Zhuo, Zhizheng; Mo, Xiao; Ma, Xiangyu; Han, Ying; Li, Haiyun

2018-05-02

To investigate the subtle functional connectivity alterations of aMCI based on AAL atlas with 1024 regions (AAL_1024 atlas). Functional MRI images of 32 aMCI patients (Male/Female:15/17, Ages:66.8±8.36y) and 35 normal controls (Male/Female:13/22, Ages: 62.4±8.14y) were obtained in this study. Firstly, functional connectivity networks were constructed by Pearson's Correlation based on the subtle AAL_1024 atlas. Then, local and global network parameters were calculated from the thresholding functional connectivity matrices. Finally, multiple-comparison analysis was performed on these parameters to find the functional network alterations of aMCI. And furtherly, a couple of classifiers were adopted to identify the aMCI by using the network parameters. More subtle local brain functional alterations were detected by using AAL_1024 atlas. And the predominate nodes including hippocampus, inferior temporal gyrus, inferior parietal gyrus were identified which was not detected by AAL_90 atlas. The identification of aMCI from normal controls were significantly improved with the highest accuracy (98.51%), sensitivity (100%) and specificity (97.14%) compared to those (88.06%, 84.38% and 91.43% for the highest accuracy, sensitivity and specificity respectively) obtained by using AAL_90 atlas. More subtle functional connectivity alterations of aMCI could be found based on AAL_1024 atlas than those based on AAL_90 atlas. Besides, the identification of aMCI could also be improved. Copyright © 2018. Published by Elsevier B.V.

Astronauts Gemar and Allen work with lower body negative pressure experiment

NASA Image and Video Library

1994-03-05

STS062-01-032 (4-14 March 1994) --- Astronaut Charles D. (Sam) Gemar, mission specialist, talks to ground controllers while assisting astronaut Andrew M. Allen with a "soak" in the Lower Body Negative Pressure (LBNP) apparatus on Columbia's middeck. The pair was joined by three other veteran NASA astronauts for 14-days of scientific research aboard the Space Shuttle Columbia in earth orbit.

Population differences in brain morphology: Need for population specific brain template.

PubMed

Rao, Naren P; Jeelani, Haris; Achalia, Rashmin; Achalia, Garima; Jacob, Arpitha; Bharath, Rose Dawn; Varambally, Shivarama; Venkatasubramanian, Ganesan; K Yalavarthy, Phaneendra

2017-07-30

Brain templates provide a standard anatomical platform for population based morphometric assessments. Typically, standard brain templates for such assessments are created using Caucasian brains, which may not be ideal to analyze brains from other ethnicities. To effectively demonstrate this, we compared brain morphometric differences between T1 weighted structural MRI images of 27 healthy Indian and Caucasian subjects of similar age and same sex ratio. Furthermore, a population specific brain template was created from MRI images of healthy Indian subjects and compared with standard Montreal Neurological Institute (MNI-152) template. We also examined the accuracy of registration of by acquiring a different T1 weighted MRI data set and registering them to newly created Indian template and MNI-152 template. The statistical analysis indicates significant difference in global brain measures and regional brain structures of Indian and Caucasian subjects. Specifically, the global brain measurements of the Indian brain template were smaller than that of the MNI template. Also, Indian brain images were better realigned to the newly created template than to the MNI-152 template. The notable variations in Indian and Caucasian brains convey the need to build a population specific Indian brain template and atlas. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Atlas-Guided Cluster Analysis of Large Tractography Datasets

PubMed Central

Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer

2013-01-01

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment. PMID:24386292

Atlas-guided cluster analysis of large tractography datasets.

PubMed

Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer

2013-01-01

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment.

Atlas-based segmentation of brainstem regions in neuromelanin-sensitive magnetic resonance images

NASA Astrophysics Data System (ADS)

Puigvert, Marc; Castellanos, Gabriel; Uranga, Javier; Abad, Ricardo; Fernández-Seara, María. A.; Pastor, Pau; Pastor, María. A.; Muñoz-Barrutia, Arrate; Ortiz de Solórzano, Carlos

2015-03-01

We present a method for the automatic delineation of two neuromelanin rich brainstem structures -substantia nigra pars compacta (SN) and locus coeruleus (LC)- in neuromelanin sensitive magnetic resonance images of the brain. The segmentation method uses a dynamic multi-image reference atlas and a pre-registration atlas selection strategy. To create the atlas, a pool of 35 images of healthy subjects was pair-wise pre-registered and clustered in groups using an affinity propagation approach. Each group of the atlas is represented by a single exemplar image. Each new target image to be segmented is registered to the exemplars of each cluster. Then all the images of the highest performing clusters are enrolled into the final atlas, and the results of the registration with the target image are propagated using a majority voting approach. All registration processes used combined one two-stage affine and one elastic B-spline algorithm, to account for global positioning, region selection and local anatomic differences. In this paper, we present the algorithm, with emphasis in the atlas selection method and the registration scheme. We evaluate the performance of the atlas selection strategy using 35 healthy subjects and 5 Parkinson's disease patients. Then, we quantified the volume and contrast ratio of neuromelanin signal of these structures in 47 normal subjects and 40 Parkinson's disease patients to confirm that this method can detect neuromelanin-containing neurons loss in Parkinson's disease patients and could eventually be used for the early detection of SN and LC damage.

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation.

PubMed

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom

2015-12-23

The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP

A probabilistic atlas of human brainstem pathways based on connectome imaging data.

PubMed

Tang, Yuchun; Sun, Wei; Toga, Arthur W; Ringman, John M; Shi, Yonggang

2018-04-01

The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles

Matching spatial with ontological brain regions using Java tools for visualization, database access, and integrated data analysis.

PubMed

Bezgin, Gleb; Reid, Andrew T; Schubert, Dirk; Kötter, Rolf

2009-01-01

Brain atlases are widely used in experimental neuroscience as tools for locating and targeting specific brain structures. Delineated structures in a given atlas, however, are often difficult to interpret and to interface with database systems that supply additional information using hierarchically organized vocabularies (ontologies). Here we discuss the concept of volume-to-ontology mapping in the context of macroscopical brain structures. We present Java tools with which we have implemented this concept for retrieval of mapping and connectivity data on the macaque brain from the CoCoMac database in connection with an electronic version of "The Rhesus Monkey Brain in Stereotaxic Coordinates" authored by George Paxinos and colleagues. The software, including our manually drawn monkey brain template, can be downloaded freely under the GNU General Public License. It adds value to the printed atlas and has a wider (neuro-)informatics application since it can read appropriately annotated data from delineated sections of other species and organs, and turn them into 3D registered stacks. The tools provide additional features, including visualization and analysis of connectivity data, volume and centre-of-mass estimates, and graphical manipulation of entire structures, which are potentially useful for a range of research and teaching applications.

volBrain: An Online MRI Brain Volumetry System

PubMed Central

Manjón, José V.; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results. PMID:27512372

volBrain: An Online MRI Brain Volumetry System.

PubMed

Manjón, José V; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results.

Magnetohydrodynamic modeling of three Van Allen Probes storms in 2012 and 2013

NASA Astrophysics Data System (ADS)

Paral, J.; Hudson, M. K.; Kress, B. T.; Wiltberger, M. J.; Wygant, J. R.; Singer, H. J.

2015-08-01

Coronal mass ejection (CME)-shock compression of the dayside magnetopause has been observed to cause both prompt enhancement of radiation belt electron flux due to inward radial transport of electrons conserving their first adiabatic invariant and prompt losses which at times entirely eliminate the outer zone. Recent numerical studies suggest that enhanced ultra-low frequency (ULF) wave activity is necessary to explain electron losses deeper inside the magnetosphere than magnetopause incursion following CME-shock arrival. A combination of radial transport and magnetopause shadowing can account for losses observed at radial distances into L = 4.5, well within the computed magnetopause location. We compare ULF wave power from the Electric Field and Waves (EFW) electric field instrument on the Van Allen Probes for the 8 October 2013 storm with ULF wave power simulated using the Lyon-Fedder-Mobarry (LFM) global magnetohydrodynamic (MHD) magnetospheric simulation code coupled to the Rice Convection Model (RCM). Two other storms with strong magnetopause compression, 8-9 October 2012 and 17-18 March 2013, are also examined. We show that the global MHD model captures the azimuthal magnetosonic impulse propagation speed and amplitude observed by the Van Allen Probes which is responsible for prompt acceleration at MeV energies reported for the 8 October 2013 storm. The simulation also captures the ULF wave power in the azimuthal component of the electric field, responsible for acceleration and radial transport of electrons, at frequencies comparable to the electron drift period. This electric field impulse has been shown to explain observations in related studies (Foster et al., 2015) of electron acceleration and drift phase bunching by the Energetic Particle, Composition, and Thermal Plasma Suite (ECT) instrument on the Van Allen Probes.

ATLAS F MISSILE FIELDS IN THE UNITED STATES, ATLAS F ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

ATLAS F MISSILE FIELDS IN THE UNITED STATES, ATLAS F- TEXAS RING OF TWELVE - Dyess Air Force Base, Atlas F Missle Site S-8, Approximately 3 miles east of Winters, 500 feet southwest of Highway 177, Winters, Runnels County, TX

Non-imaged based method for matching brains in a common anatomical space for cellular imagery.

PubMed

Midroit, Maëllie; Thevenet, Marc; Fournel, Arnaud; Sacquet, Joelle; Bensafi, Moustafa; Breton, Marine; Chalençon, Laura; Cavelius, Matthias; Didier, Anne; Mandairon, Nathalie

2018-04-22

Cellular imagery using histology sections is one of the most common techniques used in Neuroscience. However, this inescapable technique has severe limitations due to the need to delineate regions of interest on each brain, which is time consuming and variable across experimenters. We developed algorithms based on a vectors field elastic registration allowing fast, automatic realignment of experimental brain sections and associated labeling in a brain atlas with high accuracy and in a streamlined way. Thereby, brain areas of interest can be finely identified without outlining them and different experimental groups can be easily analyzed using conventional tools. This method directly readjusts labeling in the brain atlas without any intermediate manipulation of images. We mapped the expression of cFos, in the mouse brain (C57Bl/6J) after olfactory stimulation or a non-stimulated control condition and found an increased density of cFos-positive cells in the primary olfactory cortex but not in non-olfactory areas of the odor-stimulated animals compared to the controls. Existing methods of matching are based on image registration which often requires expensive material (two-photon tomography mapping or imaging with iDISCO) or are less accurate since they are based on mutual information contained in the images. Our new method is non-imaged based and relies only on the positions of detected labeling and the external contours of sections. We thus provide a new method that permits automated matching of histology sections of experimental brains with a brain reference atlas. Copyright © 2018 Elsevier B.V. All rights reserved.

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

The cognitive atlas: toward a knowledge foundation for cognitive neuroscience.

PubMed

Poldrack, Russell A; Kittur, Aniket; Kalar, Donald; Miller, Eric; Seppa, Christian; Gil, Yolanda; Parker, D Stott; Sabb, Fred W; Bilder, Robert M

2011-01-01

Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what "mental processes" exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.

The Cognitive Atlas: Toward a Knowledge Foundation for Cognitive Neuroscience

PubMed Central

Poldrack, Russell A.; Kittur, Aniket; Kalar, Donald; Miller, Eric; Seppa, Christian; Gil, Yolanda; Parker, D. Stott; Sabb, Fred W.; Bilder, Robert M.

2011-01-01

Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what “mental processes” exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain. PMID:21922006

A three-plane architectonic atlas of the rat hippocampal region.

PubMed

Boccara, Charlotte N; Kjonigsen, Lisa J; Hammer, Ingvild M; Bjaalie, Jan G; Leergaard, Trygve B; Witter, Menno P

2015-07-01

The hippocampal region, comprising the hippocampal formation and the parahippocampal region, has been one of the most intensively studied parts of the brain for decades. Better understanding of its functional diversity and complexity has led to an increased demand for specificity in experimental procedures and manipulations. In view of the complex 3D structure of the hippocampal region, precisely positioned experimental approaches require a fine-grained architectural description that is available and readable to experimentalists lacking detailed anatomical experience. In this paper, we provide the first cyto- and chemoarchitectural description of the hippocampal formation and parahippocampal region in the rat at high resolution and in the three standard sectional planes: coronal, horizontal and sagittal. The atlas uses a series of adjacent sections stained for neurons and for a number of chemical marker substances, particularly parvalbumin and calbindin. All the borders defined in one plane have been cross-checked against their counterparts in the other two planes. The entire dataset will be made available as a web-based interactive application through the Rodent Brain WorkBench (http://www.rbwb.org) which, together with this paper, provides a unique atlas resource. © 2014 Wiley Periodicals, Inc.

Consensus between Pipelines in Structural Brain Networks

PubMed Central

Parker, Christopher S.; Deligianni, Fani; Cardoso, M. Jorge; Daga, Pankaj; Modat, Marc; Dayan, Michael; Clark, Chris A.

2014-01-01

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. PMID:25356977

Voxels in the Brain: Neuroscience, Informatics and Changing Notions of Objectivity.

ERIC Educational Resources Information Center

Beaulieu, Anne

2001-01-01

Examines a subset of tools (atlases of the brain) developed in the Human Brain Project (HBP) in order to understand how the use of these tools changes the practice of science. Discusses the redefinition of what constitutes 'objective' neuroscientific knowledge according to both technological possibilities built into these tools and the constraints…

Welcome - TampaBay.WaterAtlas.org

Science.gov Websites

An edition of: WaterAtlas.orgPresented By: USF Water Institute Choose a Water Atlas Charlotte Harbor NEP Water Atlas Hillsborough County Water Atlas Lake County Water Atlas Manatee County Water Atlas Orange County Water Atlas Pinellas County Water Atlas Polk County Water Atlas Sarasota County Water Atlas

A Versatile Room-Temperature Route to Di- and Trisubstituted Allenes Using Flow-Generated Diazo Compounds**

PubMed Central

Poh, Jian-Siang; Tran, Duc N; Battilocchio, Claudio; Hawkins, Joel M; Ley, Steven V

2015-01-01

A copper-catalyzed coupling reaction between flow-generated unstabilized diazo compounds and terminal alkynes provides di- and trisubstituted allenes. This extremely mild and rapid transformation is highly tolerant of several functional groups. PMID:26013774

Van Allen Probes Science Gateway: Single-Point Access to Long-Term Radiation Belt Measurements and Space Weather Nowcasting

NASA Astrophysics Data System (ADS)

Romeo, G.; Barnes, R. J.; Ukhorskiy, A. Y.; Sotirelis, T.; Stephens, G.

2017-12-01

The Science Gateway gives single-point access to over 4.5 years of comprehensive wave and particle measurements from the Van Allen Probes NASA twin-spacecraft mission. The Gateway provides a set of visualization and data analysis tools including: HTML5-based interactive visualization of high-level data products from all instrument teams in the form of: line plots, orbital content plots, dynamical energy spectra, L-shell context plots (including two-spacecraft plotting), FFT spectra of wave data, solar wind and geomagnetic indices data, etc.; download custom multi-instrument CDF data files of selected data products; publication quality plots of digital data; combined orbit predicts for mission planning and coordination including: Van Allen Probes, MMS, THEMIS, Arase (ERG), Cluster, GOES, Geotail, FIREBIRD; magnetic footpoint calculator for coordination with LEO and ground-based assets; real-time computation and processing of empirical magnetic field models - computation of magnetic ephemeris, computation of adiabatic invariants. Van Allen Probes is the first spacecraft mission to provide a nowcast of the radiation environment in the heart of the radiation belts, where the radiation levels are the highest and most dangerous for spacecraft operations. For this purpose, all instruments continuously broadcast a subset of their science data in real time. Van Allen Probes partners with four foreign institutions who operate ground stations that receive the broadcast: Korea (KASI), the Czech republic (CAS), Argentina (CONAE), and Brazil (INPE). The SpWx broadcast is then collected at APL and delivered to the community via the Science Gateway.

Kinematic control of male Allen's Hummingbird wing trill over a range of flight speeds.

PubMed

Clark, Christopher J; Mistick, Emily A

2018-05-18

Wing trills are pulsed sounds produced by modified wing feathers at one or more specific points in time during a wingbeat. Male Allen's Hummingbird ( Selasphorus sasin ) produce a sexually dimorphic 9 kHz wing trill in flight. Here we investigate the kinematic basis for trill production. The wingtip velocity hypothesis posits that trill production is modulated by the airspeed of the wingtip at some point during the wingbeat, whereas the wing rotation hypothesis posits that trill production is instead modulated by wing rotation kinematics. To test these hypotheses, we flew six male Allen's Hummingbirds in an open jet wind tunnel at flight speeds of 0, 3, 6, 9, 12 and 14 m s -1 , and recorded their flight with two 'acoustic cameras' placed below and behind, or below and lateral to the flying bird. The acoustic cameras are phased arrays of 40 microphones that used beamforming to spatially locate sound sources within a camera image. Trill Sound Pressure Level (SPL) exhibited a U-shaped relationship with flight speed in all three camera positions. SPL was greatest perpendicular to the stroke plane. Acoustic camera videos suggest that the trill is produced during supination. The trill was up to 20 dB louder during maneuvers than it was during steady state flight in the wind tunnel, across all airspeeds tested. These data provide partial support for the wing rotation hypothesis. Altered wing rotation kinematics could allow male Allen's Hummingbird to modulate trill production in social contexts such as courtship displays. © 2018. Published by The Company of Biologists Ltd.

White matter atlas of the human spinal cord with estimation of partial volume effect.

PubMed

Lévy, S; Benhamou, M; Naaman, C; Rainville, P; Callot, V; Cohen-Adad, J

2015-10-01

Template-based analysis has proven to be an efficient, objective and reproducible way of extracting relevant information from multi-parametric MRI data. Using common atlases, it is possible to quantify MRI metrics within specific regions without the need for manual segmentation. This method is therefore free from user-bias and amenable to group studies. While template-based analysis is common procedure for the brain, there is currently no atlas of the white matter (WM) spinal pathways. The goals of this study were: (i) to create an atlas of the white matter tracts compatible with the MNI-Poly-AMU template and (ii) to propose methods to quantify metrics within the atlas that account for partial volume effect. The WM atlas was generated by: (i) digitalizing an existing WM atlas from a well-known source (Gray's Anatomy), (ii) registering this atlas to the MNI-Poly-AMU template at the corresponding slice (C4 vertebral level), (iii) propagating the atlas throughout all slices of the template (C1 to T6) using regularized diffeomorphic transformations and (iv) computing partial volume values for each voxel and each tract. Several approaches were implemented and validated to quantify metrics within the atlas, including weighted-average and Gaussian mixture models. Proof-of-concept application was done in five subjects for quantifying magnetization transfer ratio (MTR) in each tract of the atlas. The resulting WM atlas showed consistent topological organization and smooth transitions along the rostro-caudal axis. The median MTR across tracts was 26.2. Significant differences were detected across tracts, vertebral levels and subjects, but not across laterality (right-left). Among the different tested approaches to extract metrics, the maximum a posteriori showed highest performance with respect to noise, inter-tract variability, tract size and partial volume effect. This new WM atlas of the human spinal cord overcomes the biases associated with manual delineation and partial

Simultaneous skull-stripping and lateral ventricle segmentation via fast multi-atlas likelihood fusion

NASA Astrophysics Data System (ADS)

Tang, Xiaoying; Kutten, Kwame; Ceritoglu, Can; Mori, Susumu; Miller, Michael I.

2015-03-01

In this paper, we propose and validate a fully automated pipeline for simultaneous skull-stripping and lateral ventricle segmentation using T1-weighted images. The pipeline is built upon a segmentation algorithm entitled fast multi-atlas likelihood-fusion (MALF) which utilizes multiple T1 atlases that have been pre-segmented into six whole-brain labels - the gray matter, the white matter, the cerebrospinal fluid, the lateral ventricles, the skull, and the background of the entire image. This algorithm, MALF, was designed for estimating brain anatomical structures in the framework of coordinate changes via large diffeomorphisms. In the proposed pipeline, we use a variant of MALF to estimate those six whole-brain labels in the test T1-weighted image. The three tissue labels (gray matter, white matter, and cerebrospinal fluid) and the lateral ventricles are then grouped together to form a binary brain mask to which we apply morphological smoothing so as to create the final mask for brain extraction. For computational purposes, all input images to MALF are down-sampled by a factor of two. In addition, small deformations are used for the changes of coordinates. This substantially reduces the computational complexity, hence we use the term "fast MALF". The skull-stripping performance is qualitatively evaluated on a total of 486 brain scans from a longitudinal study on Alzheimer dementia. Quantitative error analysis is carried out on 36 scans for evaluating the accuracy of the pipeline in segmenting the lateral ventricle. The volumes of the automated lateral ventricle segmentations, obtained from the proposed pipeline, are compared across three different clinical groups. The ventricle volumes from our pipeline are found to be sensitive to the diagnosis.

Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study.

PubMed

Rojkova, K; Volle, E; Urbanski, M; Humbert, F; Dell'Acqua, F; Thiebaut de Schotten, M

2016-04-01

In neuroscience, there is a growing consensus that higher cognitive functions may be supported by distributed networks involving different cerebral regions, rather than by single brain areas. Communication within these networks is mediated by white matter tracts and is particularly prominent in the frontal lobes for the control and integration of information. However, the detailed mapping of frontal connections remains incomplete, albeit crucial to an increased understanding of these cognitive functions. Based on 47 high-resolution diffusion-weighted imaging datasets (age range 22-71 years), we built a statistical normative atlas of the frontal lobe connections in stereotaxic space, using state-of-the-art spherical deconvolution tractography. We dissected 55 tracts including U-shaped fibers. We further characterized these tracts by measuring their correlation with age and education level. We reported age-related differences in the microstructural organization of several, specific frontal fiber tracts, but found no correlation with education level. Future voxel-based analyses, such as voxel-based morphometry or tract-based spatial statistics studies, may benefit from our atlas by identifying the tracts and networks involved in frontal functions. Our atlas will also build the capacity of clinicians to further understand the mechanisms involved in brain recovery and plasticity, as well as assist clinicians in the diagnosis of disconnection or abnormality within specific tracts of individual patients with various brain diseases.

Potential predictors for the amount of intra-operative brain shift during deep brain stimulation surgery

NASA Astrophysics Data System (ADS)

Datteri, Ryan; Pallavaram, Srivatsan; Konrad, Peter E.; Neimat, Joseph S.; D'Haese, Pierre-François; Dawant, Benoit M.

2011-03-01

A number of groups have reported on the occurrence of intra-operative brain shift during deep brain stimulation (DBS) surgery. This has a number of implications for the procedure including an increased chance of intra-cranial bleeding and complications due to the need for more exploratory electrodes to account for the brain shift. It has been reported that the amount of pneumocephalus or air invasion into the cranial cavity due to the opening of the dura correlates with intraoperative brain shift. Therefore, pre-operatively predicting the amount of pneumocephalus expected during surgery is of interest toward accounting for brain shift. In this study, we used 64 DBS patients who received bilateral electrode implantations and had a post-operative CT scan acquired immediately after surgery (CT-PI). For each patient, the volumes of the pneumocephalus, left ventricle, right ventricle, third ventricle, white matter, grey matter, and cerebral spinal fluid were calculated. The pneumocephalus was calculated from the CT-PI utilizing a region growing technique that was initialized with an atlas-based image registration method. A multi-atlas-based image segmentation method was used to segment out the ventricles of each patient. The Statistical Parametric Mapping (SPM) software package was utilized to calculate the volumes of the cerebral spinal fluid (CSF), white matter and grey matter. The volume of individual structures had a moderate correlation with pneumocephalus. Utilizing a multi-linear regression between the volume of the pneumocephalus and the statistically relevant individual structures a Pearson's coefficient of r = 0.4123 (p = 0.0103) was found. This study shows preliminary results that could be used to develop a method to predict the amount of pneumocephalus ahead of the surgery.

Probabilistic liver atlas construction.

PubMed

Dura, Esther; Domingo, Juan; Ayala, Guillermo; Marti-Bonmati, Luis; Goceri, E

2017-01-13

Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.

A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation--With Application to Tumor and Stroke.

PubMed

Menze, Bjoern H; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-Andre; Szekely, Gabor; Ayache, Nicholas; Golland, Polina

2016-04-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM), to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as "tumor core" or "fluid-filled structure", but without a one-to-one correspondence to the hypo- or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the extended discriminative -discriminative model to be one of the top ranking methods in the BRATS evaluation.

76 FR 9636 - Franklin Financial Corporation, Inc., Glen Allen, VA; Approval of Conversion Application

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-18

... DEPARTMENT OF THE TREASURY Office of Thrift Supervision [AC-59: OTS No. H-4761] Franklin Financial Corporation, Inc., Glen Allen, VA; Approval of Conversion Application Notice is hereby given that on February 11, 2011, the Office of Thrift Supervision approved the application of Franklin Financial Corporation...

ATLAS@AWS

NASA Astrophysics Data System (ADS)

Gehrcke, Jan-Philip; Kluth, Stefan; Stonjek, Stefan

2010-04-01

We show how the ATLAS offline software is ported on the Amazon Elastic Compute Cloud (EC2). We prepare an Amazon Machine Image (AMI) on the basis of the standard ATLAS platform Scientific Linux 4 (SL4). Then an instance of the SLC4 AMI is started on EC2 and we install and validate a recent release of the ATLAS offline software distribution kit. The installed software is archived as an image on the Amazon Simple Storage Service (S3) and can be quickly retrieved and connected to new SL4 AMI instances using the Amazon Elastic Block Store (EBS). ATLAS jobs can then configure against the release kit using the ATLAS configuration management tool (cmt) in the standard way. The output of jobs is exported to S3 before the SL4 AMI is terminated. Job status information is transferred to the Amazon SimpleDB service. The whole process of launching instances of our AMI, starting, monitoring and stopping jobs and retrieving job output from S3 is controlled from a client machine using python scripts implementing the Amazon EC2/S3 API via the boto library working together with small scripts embedded in the SL4 AMI. We report our experience with setting up and operating the system using standard ATLAS job transforms.

Argonne Physics Division - ATLAS

Science.gov Websites

Strategic Plan (2014) ATLAS Gus Savard Guy Savard, Director of ATLAS Welcome to ATLAS, the Argonne Tandem users. ATLAS mission statement and strategic plan guide the operation of the facility. The strategic plan defines the facilities main goals and is aligned with the US Nuclear Physics long-range plan

Van Allen Discovery Most Important

NASA Technical Reports Server (NTRS)

Jastrow, R.

1959-01-01

The first step toward the exploration of space occurred approximately 22 months ago as a part of the International Geophysical Year. In the short interval since October, 1957, the new tools of research, the satellite and the space rocket, have produced two unexpected results of fundamental scientific importance. First, instruments placed in the Explorer satellites by James A. Van Allen have revealed the existence of layers of energetic particles in the outer atmosphere. This discovery constitutes the most significant research achievement of the IGY satellite program. The layers may provide the explanation for the aurora and other geophysical phenomena, and they will also influence the design of vehicles for manned space flight, whose occupants must be shielded against their harmful biological effects. Second, the shape of the earth has been determined very accurately with the aid of data from the first Vanguard. As a result of this investigation, we have found that our planet tends toward the shape of a pear, with its stem at the North Pole. This discovery may produce major changes in our ideas on the interior structure of the earth.

Whole-brain functional magnetic resonance imaging mapping of acute nociceptive responses induced by formalin in rats using atlas registration-based event-related analysis.

PubMed

Shih, Yen-Yu I; Chen, You-Yin; Chen, Chiao-Chi V; Chen, Jyh-Cheng; Chang, Chen; Jaw, Fu-Shan

2008-06-01

Nociceptive neuronal activation in subcortical regions has not been well investigated in functional magnetic resonance imaging (fMRI) studies. The present report aimed to use the blood oxygenation level-dependent (BOLD) fMRI technique to map nociceptive responses in both subcortical and cortical regions by employing a refined data processing method, the atlas registration-based event-related (ARBER) analysis technique. During fMRI acquisition, 5% formalin (50 mul) was injected into the left hindpaw to induce nociception. ARBER was then used to normalize the data among rats, and images were analyzed using automatic selection of the atlas-based region of interest. It was found that formalin-induced nociceptive processing increased BOLD signals in both cortical and subcortical regions. The cortical activation was distributed over the cingulate, motor, somatosensory, insular, and visual cortices, and the subcortical activation involved the caudate putamen, hippocampus, periaqueductal gray, superior colliculus, thalamus, and hypothalamus. With the aid of ARBER, the present study revealed a detailed activation pattern that possibly indicated the recruitment of various parts of the nociceptive system. The results also demonstrated the utilization of ARBER in establishing an fMRI-based whole-brain nociceptive map. The formalin induced nociceptive images may serve as a template of central nociceptive responses, which can facilitate the future use of fMRI in evaluation of new drugs and preclinical therapies for pain. (c) 2008 Wiley-Liss, Inc.

White matter lesion extension to automatic brain tissue segmentation on MRI.

PubMed

de Boer, Renske; Vrooman, Henri A; van der Lijn, Fedde; Vernooij, Meike W; Ikram, M Arfan; van der Lugt, Aad; Breteler, Monique M B; Niessen, Wiro J

2009-05-01

A fully automated brain tissue segmentation method is optimized and extended with white matter lesion segmentation. Cerebrospinal fluid (CSF), gray matter (GM) and white matter (WM) are segmented by an atlas-based k-nearest neighbor classifier on multi-modal magnetic resonance imaging data. This classifier is trained by registering brain atlases to the subject. The resulting GM segmentation is used to automatically find a white matter lesion (WML) threshold in a fluid-attenuated inversion recovery scan. False positive lesions are removed by ensuring that the lesions are within the white matter. The method was visually validated on a set of 209 subjects. No segmentation errors were found in 98% of the brain tissue segmentations and 97% of the WML segmentations. A quantitative evaluation using manual segmentations was performed on a subset of 6 subjects for CSF, GM and WM segmentation and an additional 14 for the WML segmentations. The results indicated that the automatic segmentation accuracy is close to the interobserver variability of manual segmentations.

EMIC waves covering wide L shells: MMS and Van Allen Probes observations

NASA Astrophysics Data System (ADS)

Yu, Xiongdong; Yuan, Zhigang; Huang, Shiyong; Wang, Dedong; Li, Haimeng; Qiao, Zheng; Yao, Fei

2017-07-01

During 04:45:00-08:15:00 UT on 13 September in 2015, a case of Electromagnetic ion cyclotron (EMIC) waves covering wide L shells (L = 3.6-9.4), observed by the Magnotospheric Multiscale 1 (MMS1) are reported. During the same time interval, EMIC waves observed by Van Allen Probes A (VAP-A) only occurred just outside the plasmapause. As the Van Allen Probes moved outside into a more tenuous plasma region, no intense waves were observed. Combined observations of MMS1 and VAP-A suggest that in the terrestrial magnetosphere, an appropriately dense background plasma would make contributions to the growth of EMIC waves in lower L shells, while the ion anisotropy, driven by magnetospheric compression, might play an important role in the excitation of EMIC waves in higher L shells. These EMIC waves are observed over wide L shells after three continuous magnetic storms, which suggests that these waves might obtain their free energy from those energetic ions injected during storm times. These EMIC waves should be included in radiation belt modeling, especially during continuous magnetic storms. Moreover, two-band structures separated in frequencies by local He2+ gyrofrequencies were observed in large L shells (L > 6), implying sufficiently rich solar wind origin He2+ likely in the outer ring current. It is suggested that multiband-structured EMIC waves can be used to trace the coupling between solar wind and the magnetosphere.tract type="synopsis">le type="main">Plain Language SummaryThe spatial distribution of EMIC waves is an opening question. With combined observations of MMS and Van Allen Probes, this paper has reported EMIC waves covering wide L shells. Moreover, two-band structures separated in frequencies by local He2+ gyrofrequencies were observed in large L shells (L > 6), implying sufficiently rich solar wind origin He2+ likely in the outer ring current. The result is helpful to revealing the spatial distribution and role of He2+ in excitation of EMIC waves.

Digimouse: a 3D whole body mouse atlas from CT and cryosection data

PubMed Central

Dogdas, Belma; Stout, David; Chatziioannou, Arion F; Leahy, Richard M

2010-01-01

We have constructed a three-dimensional (3D) whole body mouse atlas from coregistered x-ray CT and cryosection data of a normal nude male mouse. High quality PET, x-ray CT and cryosection images were acquired post mortem from a single mouse placed in a stereotactic frame with fiducial markers visible in all three modalities. The image data were coregistered to a common coordinate system using the fiducials and resampled to an isotropic 0.1 mm voxel size. Using interactive editing tools we segmented and labelled whole brain, cerebrum, cerebellum, olfactory bulbs, striatum, medulla, masseter muscles, eyes, lachrymal glands, heart, lungs, liver, stomach, spleen, pancreas, adrenal glands, kidneys, testes, bladder, skeleton and skin surface. The final atlas consists of the 3D volume, in which the voxels are labelled to define the anatomical structures listed above, with coregistered PET, x-ray CT and cryosection images. To illustrate use of the atlas we include simulations of 3D bioluminescence and PET image reconstruction. Optical scatter and absorption values are assigned to each organ to simulate realistic photon transport within the animal for bioluminescence imaging. Similarly, 511 keV photon attenuation values are assigned to each structure in the atlas to simulate realistic photon attenuation in PET. The Digimouse atlas and data are available at http://neuroimage.usc.edu/Digimouse.html. PMID:17228106

Functional atlas of the awake rat brain: A neuroimaging study of rat brain specialization and integration.

PubMed

Ma, Zhiwei; Perez, Pablo; Ma, Zilu; Liu, Yikang; Hamilton, Christina; Liang, Zhifeng; Zhang, Nanyin

2018-04-15

Connectivity-based parcellation approaches present an innovative method to segregate the brain into functionally specialized regions. These approaches have significantly advanced our understanding of the human brain organization. However, parallel progress in animal research is sparse. Using resting-state fMRI data and a novel, data-driven parcellation method, we have obtained robust functional parcellations of the rat brain. These functional parcellations reveal the regional specialization of the rat brain, which exhibited high within-parcel homogeneity and high reproducibility across animals. Graph analysis of the whole-brain network constructed based on these functional parcels indicates that the rat brain has a topological organization similar to humans, characterized by both segregation and integration. Our study also provides compelling evidence that the cingulate cortex is a functional hub region conserved from rodents to humans. Together, this study has characterized the rat brain specialization and integration, and has significantly advanced our understanding of the rat brain organization. In addition, it is valuable for studies of comparative functional neuroanatomy in mammalian brains. Copyright © 2016 Elsevier Inc. All rights reserved.

Explaining the Diverse Response of the Ultra-relativistic Van Allen Radiation Belt to Solar Wind Forcing

NASA Astrophysics Data System (ADS)

Mann, I. R.; Ozeke, L.; Murphy, K. R.; Claudepierre, S. G.; Rae, J.; Milling, D. K.; Kale, A.; Baker, D. N.

2017-12-01

The NASA Van Allen Probes have opened a new window on the dynamics of ultra-relativistic electrons in the Van Allen radiation belts. Under different solar wind forcing the outer belt is seen to respond in a variety of apparently diverse and sometimes remarkable ways. For example, sometimes a third radiation belt is carved out (e.g., September 2012), or the belts can remain depleted for 10 days or more (September 2014). More usually there is a sequential response of a strong and sometimes rapid depletion followed by a re-energization, the latter increasing outer belt electron flux by orders of magnitude on hour timescales during some of the strongest storms of this solar cycle (e.g., March 2013, March 2015). Such dynamics also appear to be often bounded at low-L by an apparently impenetrable barrier at L 2.8 through which ultra-relativistic electrons do not penetrate. Many studies in the Van Allen Probes era have sought explanations for these apparently diverse features, often incorporating the effects from multiple plasma waves. In contrast, we show how this apparently diverse behaviour can instead be explained by one dominant process: ULF wave radial transport. Once ULF wave transport rates are accurately specified by observations, and coupled to the dynamical variation of the outer boundary condition at the edge of the outer belt, the observed diverse responses can all be explained. However, in order to get good agreement with observations, the modeling reveals the importance of still currently unexplained very fast loss in the main phase which results in an almost total extinction of the belts and decouples pre- and post-storm ultra-relativistic electron flux on hour timescales. Similarly, varying plasmasheet source populations are seen to be of critical importance such that near-tail dynamics play a crucial role in Van Allen belt dynamics. Nonetheless, simple models incorporating accurate transport rates derived directly from ULF wave measurements are shown to

A generative probabilistic model and discriminative extensions for brain lesion segmentation – with application to tumor and stroke

PubMed Central

Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial; Riklin-Raviv, Tammy; Geremia, Ezequiel; Alberts, Esther; Gruber, Philipp; Wegener, Susanne; Weber, Marc-André; Székely, Gabor; Ayache, Nicholas; Golland, Polina

2016-01-01

We introduce a generative probabilistic model for segmentation of brain lesions in multi-dimensional images that generalizes the EM segmenter, a common approach for modelling brain images using Gaussian mixtures and a probabilistic tissue atlas that employs expectation-maximization (EM) to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model to arbitrary labels with semantic and biological meaning, such as “tumor core” or “fluid-filled structure”, but without a one-to-one correspondence to the hypo-or hyper-intense lesion areas identified by the generative model. We test the approach in two image sets: the publicly available BRATS set of glioma patient scans, and multimodal brain images of patients with acute and subacute ischemic stroke. We find the generative model that has been designed for tumor lesions to generalize well to stroke images, and the generative-discriminative model to be one of the top ranking methods in the BRATS evaluation. PMID:26599702

A new coordinate system for rodent brain and variability in the brain weights and dimensions of different ages in the naked mole-rat.

PubMed

Xiao, Jun

2007-05-15

Traditionally, the skull landmarks, i.e., bregma, lambda, and the interaural line, are the origins of the coordinate system for almost all rodent brain atlases. The disadvantages of using a skull landmark as an origin are: (i) there are differences among individuals in the alignment between the skull and the brain; (ii) the shapes of sutures, on which a skull landmark is determined, are different for different animals; (iii) the skull landmark is not clear for some animals. Recently, the extreme point of the entire brain (the tip of the olfactory bulb) has also been used as the origin for an atlas coordinate system. The accuracy of stereotaxically locating a brain structure depends on the relative distance between the structure and the reference point of the coordinate. The disadvantages of using the brain extreme as an origin are that it is located far from most brain structures and is not readily exposed during most in vivo procedures. To overcome these disadvantages, this paper introduces a new coordinate system for the brain of the naked mole-rat. The origin of this new coordinate system is a landmark directly on the brain: the intersection point of the posterior edges of the two cerebral hemispheres. This new coordinate system is readily applicable to other rodent species and is statistically better than using bragma and lambda as reference points. It is found that the body weight of old naked mole-rats is significantly bigger than that of young animals. However, the old naked mole-rat brain is not significantly heavier than that of young animal. Both brain weight and brain length vary little among animals of different weights. The disadvantages of current definition of "significant" are briefly discussed and a new expression that describes more objectively the result of statistical test is brought up and used.

William Allen Miller (1817-70): a distinguished scientist re-discovered.

PubMed

Ashley-Miller, Michael

2008-11-01

Dr William Allen Miller developed an early interest in science and astronomy at secondary school. Although qualifying in medicine, he pursued a career in Chemistry at King's College, London. A particular interest in spectrum analysis led to a collaboration with Dr Huggins in examining the spectra of stars. For this work they each received the Gold Medal of the Royal Astronomical Society. His subsequent work at King's College, the Royal Society, the Courts of Law and for various Government enterprises earned him an outstanding scientific and advisory reputation.

From the IGY to the IHY: A Changing View of the Van Allen Radiation Belts

NASA Astrophysics Data System (ADS)

Hudson, M. K.

2006-12-01

Discovery of the Van Allen radiation belts by instrumentation flown on Explorer 1 in 1958 was the first major discovery of the Space Age. A view of the belts as static inner and outer zones of energetic particles with different sources, a double-doughnut encircling the Earth, became iconic to the point that their dynamic behavior and solar connection receded from public awareness and apparent scientific import. Then the Cycle 23 maximum in solar activity arrived in 1989-1991, the first approaching the activity level of the International Geophysical Year of 1957-58, when the Van Allen belts were first discovered. Delay in launch of the NASA-Air Force Combined Radiation Release and Effects Satellite, following the Challenger accident in 1986, led to having the right instruments in the right orbit at the right time to detect prompt injection of outer belt electrons and solar energetic protons into the `slot region' between the inner and outer belts, forming new trapped populations which lasted for years in an otherwise benign location. This event in March 1991, along with the great geomagnetic storm of March 1989, and our increased dependence on space technology since the early Explorer days, led to a resurgence of interest in the Van Allen radiation belts and understanding of their connectivity to the Sun. Additional instrumentation from NASA's International Solar Terrestrial Physics Program, the Solar Anomalous and Magnetospheric Particle Explorer (SAMPEX) and IMAGE spacecraft from the Explorer program, NOAA and DOD spacecraft, and improved worldwide linkages of groundbased measurements have contributed much since 1991 to our understanding of the dynamic characteristics of the Van Allen belts. Further, the presence of continuous solar wind measurements beginning with the launch of WIND in 1994, and SOHO images of Coronal Mass Ejections and coronal hole sources of high speed solar wind flow have filled in the connection with solar activity qualitatively anticipated

Clinical outcomes and repair integrity after arthroscopic full-thickness rotator cuff repair: suture-bridge versus double-row modified Mason-Allen technique.

PubMed

Lee, Kwang Won; Yang, Dae Suk; Lee, Gyu Sang; Ma, Chang Hyun; Choy, Won Sik

2018-05-23

This retrospective study compared the clinical and radiologic outcomes of patients who underwent arthroscopic rotator cuff repairs by the suture-bridge and double-row modified Mason-Allen techniques. From January 2012 to May 2013, 76 consecutive cases of full-thickness rotator cuff tear, 1 to 4 cm in the sagittal plane, for which arthroscopic rotator cuff repair was performed, were included. The suture-bridge technique was used in 37 consecutive shoulders; and the double-row modified Mason-Allen technique, in 39 consecutive shoulders. Clinical outcomes at a minimum of 2 years (mean, 35.7 months) were evaluated postoperatively using the visual analog scale; University of California, Los Angeles Shoulder Scale; American Shoulder and Elbow Surgeons Subjective Shoulder Scale; and Constant score. Postoperative cuff integrity was evaluated at a mean of 17.7 months by magnetic resonance imaging. At the final follow-up, the clinical outcomes improved in both groups (all P < .001) but with no significant differences between the 2 groups (all P > .05). The retear rate was 18.9% in the shoulders subjected to suture-bridge repair and 12.8% in the double-row modified Mason-Allen group; the difference was not significant (P = .361). Despite the presence of fewer suture anchors, the patients who underwent double-row modified Mason-Allen repair had comparable shoulder functional outcomes and a comparable retear rate with those who underwent suture-bridge repair. Therefore, the double-row modified Mason-Allen repair technique can be considered an effective treatment for patients with medium- to large-sized full-thickness rotator cuff tears. Copyright © 2018 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

PubMed

Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

Low-energy (< 200 eV) electron acceleration by ULF waves in the plasmaspheric boundary layer: Van Allen Probes observation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Jie; Zong, Q. G.; Miyoshi, Y.

Here, we report observational evidence of cold plamsmaspheric electron (< 200 eV) acceleration by ultra-low-frequency (ULF) waves in the plasmaspheric boundary layer on 10 September 2015. Strongly enhanced cold electron fluxes in the energy spectrogram were observed along with second harmonic mode waves with a period of about 1 minute which lasted several hours during two consecutive Van Allen Probe B orbits. Cold electron (<200 eV) and energetic proton (10-20 keV) bi-directional pitch angle signatures observed during the event are suggestive of the drift-bounce resonance mechanism. The correlation between enhanced energy fluxes and ULF waves leads to the conclusions thatmore » plasmaspheric dynamics is strongly affected by ULF waves. Van Allen Probe A and B, GOES 13, GOES 15 and MMS 1 observations suggest ULF waves in the event were strongest on the dusk-side magnetosphere. Measurements from MMS 1 contain no evidence of an external wave source during the period when ULF waves and injected energetic protons with a bump-on-tail distribution were detected by Van Allen Probe B. This suggests that the observed ULF waves were probably excited by a localized drift-bounce resonant instability, with the free energy supplied by substorm-injected energetic protons. The observations by Van Allen Probe B suggest that energy transfer between particle species in different energy ranges can take place through the action of ULF waves, demonstrating the important role of these waves in the dynamical processes of the inner magnetosphere.« less

Low-energy (< 200 eV) electron acceleration by ULF waves in the plasmaspheric boundary layer: Van Allen Probes observation

DOE PAGES

Ren, Jie; Zong, Q. G.; Miyoshi, Y.; ...

2017-08-30

Here, we report observational evidence of cold plamsmaspheric electron (< 200 eV) acceleration by ultra-low-frequency (ULF) waves in the plasmaspheric boundary layer on 10 September 2015. Strongly enhanced cold electron fluxes in the energy spectrogram were observed along with second harmonic mode waves with a period of about 1 minute which lasted several hours during two consecutive Van Allen Probe B orbits. Cold electron (<200 eV) and energetic proton (10-20 keV) bi-directional pitch angle signatures observed during the event are suggestive of the drift-bounce resonance mechanism. The correlation between enhanced energy fluxes and ULF waves leads to the conclusions thatmore » plasmaspheric dynamics is strongly affected by ULF waves. Van Allen Probe A and B, GOES 13, GOES 15 and MMS 1 observations suggest ULF waves in the event were strongest on the dusk-side magnetosphere. Measurements from MMS 1 contain no evidence of an external wave source during the period when ULF waves and injected energetic protons with a bump-on-tail distribution were detected by Van Allen Probe B. This suggests that the observed ULF waves were probably excited by a localized drift-bounce resonant instability, with the free energy supplied by substorm-injected energetic protons. The observations by Van Allen Probe B suggest that energy transfer between particle species in different energy ranges can take place through the action of ULF waves, demonstrating the important role of these waves in the dynamical processes of the inner magnetosphere.« less

Comparing simulated and observed EMIC wave amplitudes using in situ Van Allen Probes’ measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saikin, A. A.; Jordanova, Vania Koleva; Zhang, J. C.

In this study, we perform a statistical study calculating electromagnetic ion cyclotron (EMIC) wave amplitudes based off in situ plasma measurements taken by the Van Allen Probes’ (1.1–5.8 R e) Helium, Oxygen, Proton, Electron (HOPE) instrument. Calculated wave amplitudes are compared to EMIC waves observed by the Electric and Magnetic Field Instrument Suite and Integrated Science on board the Van Allen Probes during the same period. The survey covers a 22-month period (1 November 2012 to 31 August 2014), a full Van Allen Probe magnetic local time (MLT) precession. The linear theory proxy was used to identify EMIC wave eventsmore » with plasma conditions favorable for EMIC wave excitation. Two hundred and thirty-two EMIC wave events (103 H +-band and 129 He +-band) were selected for this comparison. Nearly all events selected are observed beyond L = 4. Results show that calculated wave amplitudes exclusively using the in situ HOPE measurements produce amplitudes too low compared to the observed EMIC wave amplitudes. Hot proton anisotropy (Ahp) distributions are asymmetric in MLT within the inner (L < 7) magnetosphere with peak (minimum) A hp, ~0.81 to 1.00 (~0.62), observed in the dawn (dusk), 0000 < MLT ≤ 1200 (1200 < MLT ≤ 2400), sectors. Measurements of A hp are found to decrease in the presence of EMIC wave activity. A hp amplification factors are determined and vary with respect to EMIC wave-band and MLT. Lastly, He +-band events generally require double (quadruple) the measured A hp for the dawn (dusk) sector to reproduce the observed EMIC wave amplitudes.« less

New Measurements of Inner Belt Proton Flux Gradients From the Van Allen Probes Mission

NASA Astrophysics Data System (ADS)

Mazur, J. E.; O'Brien, T. P.; Looper, M. D.; George, J. S.; Blake, J. B.

2013-12-01

Prior studies of 10's of MeV inner belt protons in low Earth orbit have established that the atmospheric density gradient produces a proton flux gradient because of losses to the atmosphere and the comparable sizes of the proton qyroradius and atmosphere scale height. The observable is an east-west asymmetry in the proton flux that has been reported using many low-Earth orbit missions going back to the first nuclear emulsion flights in 1963. We will revisit this low-altitude east-west effect as well as higher-altitude gradients with new measurements from the Relativistic Proton Spectrometer (RPS) on the Van Allen Probes spacecraft. RPS is a particle spectrometer designed to measure the flux, angular distribution, and energy spectrum of protons from ~60 MeV to ~2000 MeV with good rejection of penetrating backgrounds by requiring a 10-fold coincidence in its stack of silicon detectors. The Van Allen Probes orbit allows for a survey of proton gradients not only at low altitudes but also as high as the outer trapping limit at McIlwain L shell L~3 corresponding to ~13,000 km altitude. The 60 MeV proton gyroradius varies from ~50 to 700 km in this altitude range. The 1-second sampling of RPS and the nominal 5 rpm rotation rate of the Van Allen Probes yields a sensitive measure of proton gradients. This is the first time that a single mission can address the gradients and trapping of high-energy protons throughout the inner belt. We will report on preliminary flux gradients of >61 MeV protons observed during the first year of the mission using RPS and ancillary geophysical data.

Comparing simulated and observed EMIC wave amplitudes using in situ Van Allen Probes’ measurements

DOE PAGES

Saikin, A. A.; Jordanova, Vania Koleva; Zhang, J. C.; ...

2018-02-02

In this study, we perform a statistical study calculating electromagnetic ion cyclotron (EMIC) wave amplitudes based off in situ plasma measurements taken by the Van Allen Probes’ (1.1–5.8 R e) Helium, Oxygen, Proton, Electron (HOPE) instrument. Calculated wave amplitudes are compared to EMIC waves observed by the Electric and Magnetic Field Instrument Suite and Integrated Science on board the Van Allen Probes during the same period. The survey covers a 22-month period (1 November 2012 to 31 August 2014), a full Van Allen Probe magnetic local time (MLT) precession. The linear theory proxy was used to identify EMIC wave eventsmore » with plasma conditions favorable for EMIC wave excitation. Two hundred and thirty-two EMIC wave events (103 H +-band and 129 He +-band) were selected for this comparison. Nearly all events selected are observed beyond L = 4. Results show that calculated wave amplitudes exclusively using the in situ HOPE measurements produce amplitudes too low compared to the observed EMIC wave amplitudes. Hot proton anisotropy (Ahp) distributions are asymmetric in MLT within the inner (L < 7) magnetosphere with peak (minimum) A hp, ~0.81 to 1.00 (~0.62), observed in the dawn (dusk), 0000 < MLT ≤ 1200 (1200 < MLT ≤ 2400), sectors. Measurements of A hp are found to decrease in the presence of EMIC wave activity. A hp amplification factors are determined and vary with respect to EMIC wave-band and MLT. Lastly, He +-band events generally require double (quadruple) the measured A hp for the dawn (dusk) sector to reproduce the observed EMIC wave amplitudes.« less

Automatic atlas-based three-label cartilage segmentation from MR knee images

PubMed Central

Shan, Liang; Zach, Christopher; Charles, Cecil; Niethammer, Marc

2016-01-01

Osteoarthritis (OA) is the most common form of joint disease and often characterized by cartilage changes. Accurate quantitative methods are needed to rapidly screen large image databases to assess changes in cartilage morphology. We therefore propose a new automatic atlas-based cartilage segmentation method for future automatic OA studies. Atlas-based segmentation methods have been demonstrated to be robust and accurate in brain imaging and therefore also hold high promise to allow for reliable and high-quality segmentations of cartilage. Nevertheless, atlas-based methods have not been well explored for cartilage segmentation. A particular challenge is the thinness of cartilage, its relatively small volume in comparison to surrounding tissue and the difficulty to locate cartilage interfaces – for example the interface between femoral and tibial cartilage. This paper focuses on the segmentation of femoral and tibial cartilage, proposing a multi-atlas segmentation strategy with non-local patch-based label fusion which can robustly identify candidate regions of cartilage. This method is combined with a novel three-label segmentation method which guarantees the spatial separation of femoral and tibial cartilage, and ensures spatial regularity while preserving the thin cartilage shape through anisotropic regularization. Our segmentation energy is convex and therefore guarantees globally optimal solutions. We perform an extensive validation of the proposed method on 706 images of the Pfizer Longitudinal Study. Our validation includes comparisons of different atlas segmentation strategies, different local classifiers, and different types of regularizers. To compare to other cartilage segmentation approaches we validate based on the 50 images of the SKI10 dataset. PMID:25128683

A Diverging DOS Strategy Using an Allene-Containing Tryptophan Scaffold and a Library Design that Maximizes Biologically Relevant Chemical Space While Minimizing the Number of Compounds

PubMed Central

Painter, Thomas O.; Wang, Lirong; Majumder, Supriyo; Xie, Xiang-Qun; Brummond, Kay M.

2011-01-01

A diverging diversity-oriented synthesis (DOS) strategy using an allene-containing tryptophan as a key starting material was investigated. An allene-yne substituted derivative of tryptophan 12 gave indolylmethylazabicyclooctadiene 17 when subjected to a microwave-assisted allenic [2 + 2] cycloaddition reaction. This same tryptophan-derived precursor afforded an indolylmethyldihydrocyclopentapyridinone 14 when subjected to a rhodium(I)-catalyzed cyclocarbonylation reaction and an indolylmethylpyrrolidinocyclopentenones 16 when reacted with molybdenum hexacarbonyl. Construction of allenic tetrahydro-β-carboline scaffolds via a Pictet-Spengler reaction and subsequent silver(I)-catalyzed cycloisomerization afforded tetrahydroindolizinoindoles (21). Attachment of allene and alkyne groups to the tetrahydro-β-carboline followed by a microwave-assisted allenic [2 + 2] cycloaddition reaction provided tetrahydrocyclobutaindoloquinolizinones 24 and the tetrahydrocyclopentenone indolizinoindolone 26 when reacted with molybdenum hexacarbonyl. These six scaffolds were used as a template for the construction of a virtual library of 11,748 compounds employing 44 indoles, 12 aldehydes, and 51 alkynes. Diversity analyses using a combination of cell-based chemistry space computations using BCUT (Burden (B) CAS (C) Pearlman at the University of Texas (UT)) metrics and Tanimoto coefficient (Tc) similarity calculations using two-dimensional (2D) fingerprints showed that the compounds in the virtual library occupied new chemical space when compared to the 327,000 compounds in the molecular libraries small molecule repository (MLSMR). A subset of fifty-three compounds was identified from the virtual library using the DVS package of Sybyl 8.0; this subset represents the most diverse compounds within the chemical space defined by these compounds and will be synthesized and screened for biological activity. PMID:21332123

Coherent population transfer in multi-level Allen-Eberly models

NASA Astrophysics Data System (ADS)

Li, Wei; Cen, Li-Xiang

2018-04-01

We investigate the solvability of multi-level extensions of the Allen-Eberly model and the population transfer yielded by the corresponding dynamical evolution. We demonstrate that, under a matching condition of the frequency, the driven two-level system and its multi-level extensions possess a stationary-state solution in a canonical representation associated with a unitary transformation. As a consequence, we show that the resulting protocol is able to realize complete population transfer in a nonadiabatic manner. Moreover, we explore the imperfect pulsing process with truncation and display that the nonadiabatic effect in the evolution can lead to suppression to the cutoff error of the protocol.

Ion Spectral Structures Observed by the Van Allen Probes and Cluster

NASA Astrophysics Data System (ADS)

Ferradas, C.; Zhang, J.; Luo, H.; Kistler, L. M.; Spence, H. E.; Larsen, B.; Skoug, R. M.; Funsten, H. O.; Reeves, G. D.

2014-12-01

During the last decades several missions have recorded the presence of dynamic spectral features of energetic ions in the inner magnetosphere. Previous studies have revealed single "nose-like" structures occurring alone and simultaneous nose-like structures (up to three). In this study we also include signatures of new types of ion structure, namely "trunk-like" and "tusk-like" structures. All the ion structures are named after the characteristic shapes of energy bands or gaps in the energy-time spectrograms of in situ measured ion fluxes. They constitute the observational signatures of ion acceleration, transport, and loss in the global magnetosphere. Multi-spacecraft analysis of these structures is important to understand their spatial distribution and temporal evolution. Mass spectrometers onboard Cluster (in a polar orbit) and the Van Allen Probes (in an equatorial orbit) measure energetic hydrogen, helium, and oxygen ions near the inner edge of the plasma sheet, where these ion structures are observed. We present a statistical study of the ion structures, using >1-year measurements from the two missions during the Van Allen Probes era. The results provide important details about the spatial distribution (dependence on geocentric distance and magnetic local time), spectral features of the structures (e.g., characteristic energy and differences among species), and geomagnetic and solar wind conditions under which these structures occur.

Statistics of EMIC Rising Tones Observed by the Van Allen Probes

NASA Astrophysics Data System (ADS)

Sigsbee, K. M.; Kletzing, C.; Smith, C. W.; Santolik, O.

2017-12-01

We will present results from an ongoing statistical study of electromagnetic ion cyclotron (EMIC) wave rising tones observed by the Van Allen Probes. Using data from the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) fluxgate magnetometer, we have identified orbits by both Van Allen Probes with EMIC wave events from the start of the mission in fall 2012 through fall 2016. Orbits with EMIC wave events were further examined for evidence of rising tones. Most EMIC wave rising tones were found during H+ band EMIC wave events. In Fourier time-frequency power spectrograms of the fluxgate magnetometer data, H+ band rising tones generally took the form of triggered emission type events, where the discrete rising tone structures rapidly rise in frequency out of the main band of observed H+ EMIC waves. A smaller percentage of EMIC wave rising tone events were found in the He+ band, where rising tones may appear as discrete structures with a positive slope embedded within the main band of observed He+ EMIC waves, similar in appearance to whistler-mode chorus elements. Understanding the occurrence rate and properties of rising tone EMIC waves will provide observational context for theoretical studies indicating that EMIC waves exhibiting non-linear behavior, such as rising tones, may be more effective at scattering radiation belt electrons than ordinary EMIC waves.

Atlas-guided volumetric diffuse optical tomography enhanced by generalized linear model analysis to image risk decision-making responses in young adults.

PubMed